Search

Exploratory learning depends on several e-learning technologies to enable students to direct their learning. However, the educational search engines of e-learning platforms are inspired by exploratory learning approach. Thus, their search is characterized by learning and investigation. The purpose of this paper is to explore what is considered to be deep connection between exploratory search and educational search engine since they are two complementary subjects. This relation remains at the heart of the development of exploratory learning and investigations. The paper concludes by highlighting the importance of the learning and investigation of knowledge in exploratory search for educational search engine and give other perspectives to improve this practice.

This paper argues that medium for information access becomes central to library and information science. The author discusses the notion of medium, medium neutrality, and personalization and suggests that the dominating paradigm of providing fast, efficient, and neutral systems and services for retrieving information has sidetracked opportunities to explore the impact of medium on information access. The paper makes three specific recommendations for library and information science education: be skeptical, slow down, and understand classification.

We read with considerable interest the study by Gusenbauer and Haddaway (Gusenbauer and Haddaway, 2020, Research Synthesis Methods, doi:10.1002/jrsm.1378) comparing the systematic search qualities of 28 search systems, including Google Scholar (GS) and PubMed. Google Scholar and PubMed are the two most popular free academic search tools in biology and chemistry, with GS being the number one search tool in the world. Those academics using GS as their principal system for literature searches may be unaware of research which enumerates five critical features for scientific literature tools that greatly influenced Gusenbauer's 2020 study. Using this list as the framework for a targeted comparison between just GS and PubMed, we found stark differences which overwhelmingly favored PubMed. In this comment, we show that by comparing the characteristics of the two search tools, features that are particularly useful in one search tool, but are missing in the other, are strikingly spotlighted. One especially popular feature that ubiquitously appears in GS, but not in PubMed, is the forward citation search found under every citation as a clickable "Cited by N" link. We seek to improve the PubMed search experience using two approaches. First, we request that PubMed add "Cited by N" links, making them as omnipresent as the GS links. Second, we created an open-source command-line tool, "pmidcite," which is used alongside PubMed to give information to researchers to help with the choice of the next paper to examine, analogous to how GS's "Cited by N" links help to guide users. Find "pmidcite" at https://github.com/dvklopfenstein/pmidcite. [For the original study, "Which Academic Search Systems Are Suitable for Systematic Reviews or Meta-Analyses? Evaluating Retrieval Qualities of Google Scholar, PubMed, and 26 Other Resources," see EJ1253055.]

Introduction: Studies have indicated that users' text highlighting behaviour can be further manipulated to improve the relevance of retrieved results. This article reports on a study that examined users' text highlight frequency, length and users' copy-paste actions. Method: A binary voting mechanism was employed to determine the weights for the feedback, which were then used to re-rank the original search results. A search engine prototype was built using the Communications of the ACM test collection, with the well-known BM25 acting as the baseline model. Analysis: The proposed enhanced model's performance was evaluated using the mean average precisions and F-score metrics, and results were compared at the top 5, 10 and 15. Additionally, comparisons were also made based on the number of terms used in a query, that is single, double and triple terms. Results: The findings show that the enhanced model significantly outperformed BM25, and the rest of the models at all document levels. To be specific, the enhanced model showed significant improvements over the frequency model. Additionally, retrieval relevance was found to be the best when the query length is two. Conclusions: Users' post-click behaviour may serve as a significant indicator of their interests, and thus can be used to improve the relevance of the retrieved results. Future studies could look into further extending this model by including other post-click behaviour such as printing or saving. [Paper presented at the Information Seeking in Context (ISIC): The Information Behaviour Conference, Part 1 (11th, Zadar, Croatia, September 20-23, 2016).]

Introduction: This paper investigates techniques used by children in year 4 (age eight to nine) of a UK primary school to reformulate their queries, and how they use information retrieval systems to support query reformulation. Method: An in-depth study analysing the interactions of twelve children carrying out search tasks in a primary school lesson; including observations, search recordings, post-task interviews and teacher interview. Analysis. The search screen recordings were analysed for task performance. The queries were categorised using both Broder's taxonomy (2002) and query reformulation type schemes. The interviews and observations were analysed inductively using thematic analysis. Results: Children reformulated queries by switching information retrieval system, extracting information from search results, and by using "did you mean" and auto-complete functionality. The children also reformulated queries by using previous queries, correcting errors, and making their queries more specific. The type of query reformulation support the children used varied according to the type of query entered, with children submitting both question queries and broad-based topic queries. Conclusions: The children mostly reformulated queries based on their interactions with information retrieval systems, rather than their prior knowledge. Search systems could further support children by (1) tailoring tools to the type of query (question or broad-based) entered, (2) making suggestions for the narrowing of queries as the children found this particularly difficult (3) accommodating children's linear scanning of search results as this led to unnecessary query reformulations. [This paper was published in: "Proceedings of ISIC: The Behaviour Conference" (Leeds, England, Sep 2-5, 2014), Part 2, Paper isic31.]

This paper explores the creation and content of apps about Donald Trump (n=412) published in Google Play between June 2015 and January 2018. The relevance of the study stems from both its objectives and its methodology. On the one hand, the aim was to characterise the profile, motivations and purposes of the developers of Donald Trump apps; and on the other, to identify the main features of the discourses in the most downloaded apps. The study relied on two resources: a qualitative questionnaire of open questions for developers (n=376), and a quantitative analysis of the content of apps that exceeded 5,000 downloads (n=117). The questionnaire identified the influence of political current affairs in the developers' ideological and economic motivations, while the content analysis revealed the trends found over time, as well as the themes, discourses and ideological positioning of the most popular apps about Donald Trump. The findings provide an empirical basis for how the content of these apps was articulated with the news; the influence of content that went viral; hegemonic discourses; and the role played by developers of new expressive, commercial, informative and persuasive proposals in the intersection between mobile apps and political campaigns.

The research examined the use of Information Retrieval Tools (IRTs) by the post graduate students of Mehran University of Engineering and Technology. The research used descriptive survey and was carried out over a period of six months between August 2016 and January, 2017. The sample size comprise of 2,000 postgraduate students which were randomly selected from different faculties/institutes and were served with copies of the questionnaire. A total of 1,970 copies of useable questionnaire were retrieved which represent 98.5% response rate. The responses were collated and analyzed using frequency counts and percentages. The outcome shows that respondents make use of IRTs for a variety of purposes and that university library's user education and information literacy program forms the key source of their knowledge of IRTs' usage. Through it, it can be safely concluded that the university library plays major role in assisting the students to make use of IRTs. Secondary findings show that the main IRTs made use of by the respondents is the Internet Search Engines. Furthermore findings of the study also revealed that the use of the tools has impacted positively on their social and academic life and has also enhanced their global knowledge of different issues. The major constraint to student's use of the tools is that of Internet fluctuations. The paper concludes with recommendations on the need to give training on the use of IRTs to students.

Searching for relevant material on the internet has become a big difficulty with the growing number of internet users and the large volume of data available on the internet. Traditional search engines return a lot of irrelevant results in response to a user's search query, wasting a lot of time and effort because the context and semantics of the user's request are not examined. This emphasizes the requirement for an embedded approach in the search engine, allowing semantic web search. Keyword based search engines fetch online pages by comparing the tokens in the user query to the tokens in the web documents. This strategy has several flaws. To overcome these obstacles, the suggested system employs semantic search using a Sentence transformer model. The system that has been proposed can speed up data retrieval and improve data searching to provide relevant outcomes to the user. The proposed model uses the arXiv dataset which contains an archive of research papers and using BERT and FAISS, it gives relevant research paper titles as the output to the query. For semantic retrieval of data, the model behaves as a vector-based search engine. This vector-based model will save time and give efficient results to the user's query. [ABSTRACT FROM AUTHOR]

Users of research databases, such as CiteSeerX, Google Scholar, and Microsoft Academic, often search for papers using a set of keywords. Unfortunately, many authors avoid listing sufficient keywords for their papers. As such, these applications may need to automatically associate good descriptive keywords with papers. When the full text of the paper is available this problem has been thoroughly studied. In many cases, however, due to copyright limitations, research databases do not have access to the full text. On the other hand, such databases typically maintain metadata, such as the title and abstract and the citation network of each paper. In this paper we study the problem of predicting which keywords are appropriate for a research paper, using different methods based on the citation network and available metadata. Our main goal is in providing search engines with the ability to extract keywords from the available metadata. However, our system can also be used for other applications, such as for recommending keywords for the authors of new papers. We create a data set of research papers, and their citation network, keywords, and other metadata, containing over 470 K papers with and more than 2 million keywords. We compare our methods with predicting keywords using the title and abstract, in offline experiments and in a user study, concluding that the citation network provides much better predictions. [ABSTRACT FROM AUTHOR]

This paper reports on a guided navigation system built on the textbook search engine developed at Anadolu University to support distance education students. The search engine uses Turkish Language specific language processing modules to enable searches over course material presented in Open Education Faculty textbooks. We implemented a guided navigation engine by using query log mining to our application. It makes use of previous users' sessions to help students find information they are looking for by using fewer queries. We used item-based similarity to do query recommendation. This paper describes the search application, query expansion and evaluation of the system over existing query logs. We show that our system suggested relevant queries with a success rate of 85%. (Contains 5 figures and 3 tables.)

Purpose: The purpose of this paper is to investigate the use of meta-tags by the leading higher educational institutions (HEIs). It explores the various kinds of messages conveyed by HEIs in the meta-description tags of their website homepage. It further examines that whether the messages conveyed by HEIs are in accordance with the prospective students' perspective. Design/methodology/approach: A list of leading 200 universities was procured from the website of "The Times Higher Education". Meta-keywords and meta-description tags of the HEIs websites' homepage were drawn using online software. Descriptive analysis of the meta-tags was conducted to analyze their use by HEIs. Quantitative content analysis tool was applied to understand the messages conveyed by HEIs. Findings: Meta-description tags are defined by more than half (58.79 percent), whereas meta-keywords are written by approximately a quarter (27.47 percent) of HEIs on their homepage. While defining their meta-description tags, HEIs frequently used words related to the themes such as institution, focus area, academic programs, image building, geography, student group and environment. Practical implications: It will help the HEIs to understand the importance of meta-tags. Moreover, HEIs will be able to define their meta-description tags better. Originality/value: This is the first research paper to explore and analyze the meta-tags of the HEIs websites.

Introduction: In the big data age, we have to deal with a tremendous amount of information, which can be collected from various types of sources. For information search systems such as Web search engines or online digital libraries, the collection of documents becomes larger and larger. For some queries, an information search system needs to retrieve a large number of documents. On the other hand, very often people are only willing to visit no more than a few top-ranked documents. Therefore, how to develop an information search system with desirable efficiency and effectiveness is a research problem. Method: In this paper, we focus on the data fusion approach to information search, in which each component search model contributes a result and all the results are combined by a fusion algorithm. Through empirical study, we are able to find a feasible combination method that balances effectiveness and efficiency in the context of data fusion. Analysis: It is a multi-optimisation problem that aims to balance effectiveness and efficiency. To support this, we need to understand how these two factors affect each other and to what extent. Results. Using some groups of historical runs from TREC to carry out the experiment, we find that using much less information (e.g., less than 10% of the documents in the experiment), good efficiency is achievable with marginal loss on effectiveness. Conclusions: We consider that the findings from our experiment are informative and this can be used as a guideline for providing more efficient search service in the big data environment.

The nature of the information seeking behaviour of the teachers engaged in General Degree Colleges and Teachers' Training Colleges affiliated to West Bengal State University, India, is critically analysed in the present study. The descriptive analysis is based on well structured, close-ended questionnaires which were distributed among 450 teachers. 408 of them responded from whom 376 work in General Degree Colleges and 32 in Teachers' Training Colleges. The analysis of the data shows that teachers still depend mainly on printed documents, but a changing attitude is taking place in the current ICT environment as they also start to depend on electronic documents for meeting their information needs. This paper also explores the sources used by the teachers of both groups for research activities, focusing on the variability in the use of such sources of information. Additionally, this study reveals the attitudes of the teachers towards the services provided by the libraries. It is recommended that the college libraries are restructured with internet facilities and sufficient resources, in order to meet the information needs of the college teachers. In this context, the college librarians should provide basic software training to the users, to help them access the electronic sources.

The number of published findings in biomedicine increases continually. At the same time, specifics of the domain's terminology complicates the task of relevant publications retrieval. In the current research, we investigate influence of terms' variability and ambiguity on a paper's likelihood of being retrieved. We obtained statistics that demonstrate significance of the issue and its challenges, followed by presenting the sci.AI platform, which allows precise terms labeling as a resolution. [ABSTRACT FROM AUTHOR]

The Internet has increasingly influenced the information-seeking behavior of students in higher education over the past few decades. The mass availability of information on the web has seen significant changes in the electronic information needs, information retrieval, and communication patterns (information seeking behavior) of university students. The easy-to-use Internet promotes more information-seeking while constantly attracting more new users, and achieves this immeasurably faster than traditional repositories. This has catapulted the Internet to the top of the pile of current information resources. This paper aims to compare information-seeking behavior on the Internet between arts and science undergraduate students in one of the major universities in Iran. Two hundred and fifty arts and science undergraduate students at Islamic Azad University were selected using a stratified sampling technique. The average age of the students was 24.11 (arts students) and 23.34 (science students). Approximately 43% of respondents were male and 57% were female. The results indicated that science students had a higher proficiency of using Internet search strategies than did the art students. Overall, this study suggests the need for improvements in Internet-related curricula for undergraduate students.

Question answering systems have frequently been explored for educational use. However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. However, current NLP technology involves intensive computing and thus it is hard to meet the real-time demand of traditional search. This paper introduces a question answering (QA) system particularly suited for delayed-answered questions that are typical in certain asynchronous online and distance learning settings. We exploit the communication delay between student and instructor and propose a solution that integrates into an organization's existing learning management system. We present how our system fits into an online and distance learning situation and how it can better assist supporting students. The prototype system and its running results show the perspective and potential of this research. (Contains 4 tables, 12 figures and 3 footnotes.)

Personal learning environment (PLE) solutions aim at empowering learners to design (ICT and web-based) environments for their learning activities, mashing-up content and people and apps for different learning contexts. Widely used in other application areas, recommender systems can be very useful for supporting learners in their PLE-based activities, to help discover relevant content, peers sharing similar learning interests or experts on a specific topic. In this paper we examine the utilization of recommender technology for PLEs. However, being confronted by a variety of educational contexts we present three strategies for providing PLE recommendations to learners. Consequently, we compare these recommender strategies by discussing their strengths and weaknesses in general. (Contains 1 table and 4 figures.)

Rank Aggregation techniques have found wide applications for metasearch along with other streams such as Sports, Voting System, Stock Markets, and Reduction in Spam. This paper presents the optimization of rank lists for web queries put by the user on different MetaSearch engines. A metaheuristic approach such as Genetic algorithm based rank aggregation technique has been proposed and implemented in MATLAB for Kendall-tau as (GKTu) and Spearman's foot rule as (GSFD) distance measures. A comparative analysis has been carried out between ranked lists for with and without GA on the basis of simulated results. From the results it has been found that proposed GA optimized rank list (for a particular query on the basis of minimum distance) is better than the conventional methods. In addition, a word association technique i.e., AND-OR operator has been applied on each query. The results are investigated in comparison to non- logic operators for the same query.

Purpose: The purpose of this paper is to introduce the notion of social search as a new concept, drawing upon the patterns of web search behaviour. It aims to: define social search; present a taxonomy of social search; and propose a user-centred social search method. Design/methodology/approach: A mixed method approach was adopted to investigate and conceptualise the notion of social search. A review of literature on social search was carried out to identify the key trends and topics. A model of online collaboration was adopted to delineate the types and categories of social search. Four use case scenarios were developed to provide a more pragmatic approach to the understanding of social search. Findings: The developed taxonomy of social search reveals important similarities and differences between many social search systems. This analysis reveals a gap in social search approaches. A practical method was identified that allows users to directly leverage social search without special features built into search engines. Research limitations/implications: For feasibility reasons, Google was used as an example of a search system that can be used for carrying out social searches. Practical implications: The paper provides several practical implications for web searchers as well as web designers. In particular, some recommendations are provided for the design of search engines, digital libraries and browser add-ons. Social implications: The study demonstrates the value and power of "collective intelligence" in web search. It shows how general web searches can be enhanced through using socially enhanced web-based tools such as social bookmarking systems, social tagging services and social media sites. Originality/value: This is the first study that provides a granular analysis of the notion of social search and puts forward a taxonomy of social search. The use cases developed and reported are created based on real search topics, and show the value and validity of the approach taken. (Contains 1 table and 6 figures.)

Purpose: This paper aims to present the semantic content identifier (SCI), a permanent identifier, computed through a linear-time onion-peeling algorithm that enables the extraction of semantic features from a text, and the integration of this information within the permanent identifier. Design/methodology/approach: The authors employ SCI to propose a mechanism for simultaneously checking the authenticity and degrees of similarity between different information objects, and present an empirical investigation of the method. A management scenario for the control of the authentication process and the detection of the degree of violation of documents is proposed. Findings: Such a mechanism could be adopted as a component of libraries' strategy for the protection of the copyrights for documents published on the web. Practical implications: The use of the proposed numeric code can be utilised efficiently as a constituent part of the digital object identifier (DOI) system, making its computation more efficient and meaningful. Originality/value: The identifier proposed in the paper can result in a more efficient index for identifying and retrieving objects in a digital library, as well as online repositories and commercial applications that can handle information retrieval requests more effectively. (Contains 8 figures and 3 notes.)

Purpose: Image searching is a common activity for web users. Search engines offer image retrieval services based on textual queries. Previous studies have shown that web searching is more demanding when the search is not in English and does not use a Latin-based language. The aim of this paper is to explore the behaviour of the major search engines in image retrieval using Greek text queries and to present and evaluate an image metasearcher that combines semantically similar queries to improve the relevance in image retrieval. Design/methodology/approach: Initially the image retrieval capabilities (based on the number of items retrieved and their relevance) of search engines in Greek queries is studied with a number of semantically similar queries which differ in morphology. Then a system that produces semantically similar queries and merges their results is presented and the increase in relevance is measured. For the purpose of this paper, a number of queries suggested by a few students are run through the presented metasearcher and directly in the search engines. The participants of the evaluation study measured the precision in both cases. Findings: The initial evaluation revealed that search engines retrieve different results in queries that differ in morphology or in grammar but still express exactly the same information need. Omission of diacritics affects the retrieval negatively as well. The study showed that the number of relevant images increases by combining the results of queries that differ in morphology. Originality/value: The findings of this study could be applicable to other complex non-Latin languages based, for example, on the Cyrillic alphabet. The presented metasearcher is a framework on how to expand the image retrieval capabilities of existing search engines. Its modular nature allows the straightforward integration of other techniques that are tailored to the characteristics of specific natural languages.

There has been a proliferation of new research discovery tools that aid scientists in finding relevant publications. To obtain a general overview of this development, this article generates a conceptual typology of all possible research discovery tools by drawing from the information-theoretical concepts of redundancy/variety. Bibliometric links between scholarly publications can thus exhibit 'redundancy' (i.e. expectable linkages between academic works) or 'variety' (i.e. original co-occurrence patterns). On the redundancy-reproducing end of the typology are machines that harness extant co-citations or keyword queries, such as academic search engines and paper recommender systems. The variety end of the spectrum harbours services that enable categorial browsing or that suggest publications randomly, such as journals' tables of contents or random paper bots. The typology has implications for understanding how the design of research discovery platforms may ultimately shape aggregate citational networks of science. [ABSTRACT FROM AUTHOR]

This paper presents a novel concept--a Web search environment as an interactive learning environment for graduation projects. The paper addresses the question of an appropriate learning environment for writing graduation projects in universities: Can it be defined? What should it be? How should it look? How and when should it be used? The premise presented is that one of the best learning environments for writing original, high academic level graduation projects already exists and is widely used--the Web search capability and its environment. Asurvey of this subject and its analysis is presented. A survey questionnaire is appended. (Contains 2 tables and 3 figures.)

Findings from a study of users' multitasking searches on Web search engines include: multitasking searches are a noticeable user behavior; multitasking search sessions are longer than regular search sessions in terms of queries per session and duration; both Excite and AlltheWeb.com users search for about three topics per multitasking session and submit about four to five queries per topic; there is a variety of search topics in multitasking search sessions. (Author/AEF)

Tests the use of questions as a technique in the query specification process. Using a within-subjects design, 48 people interacted with a modified Google interface to solve four information problems in four domains. Half the tasks were entered as typical keyword queries, and half as questions or statements. Results suggest the typical search box is a barrier to the creation of enriched queries. (Author/AEF)

Examines the differences between Web image and textual queries, and attempts to develop an analytic model to investigate their implications for Web image retrieval systems. Provides results that give insight into Web image searching behavior and suggests implications for improvement of current Web image search engines. (AEF)

Reports results from a project that investigated the influence of two types of expertise--knowledge of the search domain and experience of the Web search engines--on students' use of a Web search engine. Results showed participants with good knowledge in the domain and participants with high experience of the Web had the best performances. (AEF)

Flexibility in query handling can be important if one types a search engine query that is misspelled, contains terms not in the database, or requires knowledge of a controlled vocabulary. Presents results of experiments that suggest the optimal form of similarity functions that are applicable to the task of phrase based retrieval to find either synonymous or closely related phrases. (AEF)

Reports on patterns and sequences of query reformulation based on query logs from a Web search engine. Results show that while most query reformulation involves content changes, about 15% of reformulation is related to format modifications. Six patterns of query reformulation emerged as a result of sequence analysis: specified, parallel, generalized, dynamic, format, and alternative. Each is discussed with definitions and examples. (AEF)

Provides an up-to-date survey of the capabilities of the major 16 search engines with respect to the types of information extraction tasks that would be useful in Web data mining and cybermetrics, and analyzes two sets of domain counts for internal consistency between results. (AEF)

Inquiry-Based Learning (IBL) is an effective approach for promoting active learning. When inquiry-based learning is incorporated into instruction, teachers provide guiding questions for students to actively explore the required knowledge in order to solve the problems. Although the World Wide Web (WWW) is a rich knowledge resource for students to explore using search engines, it is hard for students to filter out required knowledge from the unorganized web pages and the huge number of search results. In this paper, an inquiry-based learning support system with two advanced knowledge exploration modules, namely the Q&A module and the Segmented Supplemental Material (SSM) module, is proposed and developed to assist students' inquiry-based learning. This study also evaluates the effects of the proposed system on students' learning achievement and learning efficiency with the various supports provided by the proposed system. Experiments were undertaken on a "Computer Science" course for first year undergraduate students. The experimental results show that with the support of the two advanced modules, both the students' learning achievement and their learning efficiency were enhanced.

This paper discusses the provision of flexible querying facilities over heterogeneous data arising from lifelong learners' educational and work experiences. A key aim of such querying facilities is to allow learners to identify possible choices for their future learning and professional development by seeing what others have done. We motivate and describe the development of a prototype system, called ApproxRelax, that provides users with a graphical facility for incrementally constructing their queries and that supports both query approximation and query relaxation, thus allowing for flexible matching of users' queries against the data provided by other learners. We show how the system is able to return results in ranked order of their "distance" from the user's query. Our approach is novel both in its aim of supporting lifelong learners in reflecting on their learning and career choices, and also in its technical foundations that combine for the first time query approximation and query relaxation techniques for querying semistructured data. (Contains 16 figures and 2 footnotes.)

This paper presents the results from a quantitative and systematic analysis comparing the online usage of an e-reference and an e-monograph collection. A very strong relationship exists between size and usage: the larger the collection, the greater the usage. An equally strong relationship exists between searches and viewings, meaning that the more there are searches performed, the more will full-text content be viewed. The smaller e-reference collection has also seen significantly greater use proportional to its size compared to the much larger e-monograph collection. E-monographs have not seen significant usage until after the addition of very large academic e-book packages. (Contains 5 tables, 3 footnotes and 5 figures.)

Purpose: This study is an attempt to develop an automatic identification method for Arabic web queries and divide them into several query types using data mining. In addition, it seeks to evaluate the impact of the academic environment on using the internet. Design/methodology/approach: The web log files were collected from one of the higher institute's servers over a one-month period. A special program was designed and implemented to extract web search queries from these files and also to automatically classify Arabic queries into three query types (i.e. Navigational, Transactional, and Informational queries) based on predefined specifications for each type. Findings: The results indicate that students are slowly and gradually using the internet for more relevant academic purposes. Tests showed that it is possible to automatically classify Arabic queries based on query terms, with 80.6 per cent to 80.2 per cent accuracy for the two phases of the test respectively. In their future strategies, Jordanian universities should apply methods to encourage university students to use the internet for academic purposes. Web search engines in general and Arabic search engines in particular may benefit from the proposed classification method in order to improve the effectiveness and relevancy of their results in accordance with users' needs. Originality/value: Studying internet web logs has been the subject of many papers. However, the particular domain, and the specific focuses on this research are what can distinguish it from the others. (Contains 9 figures and 22 tables.)

The semantic web brings a new opportunity for efficient information organization and search. To meet the special requirements of the educational field, this paper proposes an intelligent search engine enabled by educational semantic support service, where three kinds of searches are integrated into Educational Information Intelligent Search (EIIS) framework, and web-based resources and local e-resources are both identically semantically processed. During the design, the EIISReasoning and its relevant rule sets are constructed to automatically reason semantic concepts to diverse levels by a semantic factor and a response time factor. Furthermore, the EIISRanking algorithm applies two-level ranking by a factor of semantic similarity, and the same relevance is differentiated in terms of the educational field's needs. The experiments show that the EIIS engine with semantic services has a better precision rate and improved ranking performance. (Contains 2 tables and 13 figures.)

In this paper, we propose a syntax-based text retrieval system for on-line language learning and use a fast regular expression search engine as its main component. Regular expression searches provide more scalable querying and search results than keyword-based searches. However, without a well-designed index scheme, the execution time of regular expression search would be unacceptable to users. Our methods are based on Cho and Rajagopalan (2002) and we introduce some modifications, such as a presuf index constructing algorithm and a method for deciding minimum filter factor, to meet the requirements of our syntax-based text retrieval system. The experiment results show the index space size is small and the performance of syntax-based sample queries show significant improvements over benchmark results. A user-friendly query generator is designed to support users who have no background knowledge of regular expressions. (Contains 3 tables and 3 figures.)

This paper describes an autonomous citation index named CitEc that has been developed by the authors. The system has been tested using a particular type of grey literature (GL) i.e. working papers available in the RePEc - Research Papers in Economics - digital library. Both its architecture and performance are analysed in order to determine if the system has the quality required to be used for information retrieval and for the extraction of bibliometric indicators. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the behaviour of the Egyptian scholars while accessing electronic resources through two federated search tools. The main purpose of this article is to provide guidance for federated search tool technicians and support teams about user issues, including the need for training. Design/methodology/approach: Log files were exploited to examine the behaviour of users of information retrieval systems. This study examined two log files extracted from federated search tools available to the Egyptian scholars' community for accessing electronic resources. A data mining approach was implemented to investigate user behaviour through deep analysis of these logs. Findings: Results show that: none of the available tools provide error messages for dummy queries; most of the Egyptian scholars had short queries; Boolean operators are not used in about 50 per cent of the queries; federated search tools do not provide techniques for query reformation; the optimal days for system maintenance are the non-weekend vacations; and early morning is the best time for maintenance. Practical implications: To maximise the value of the federated search tools by understanding user trends when utilising federated search tools. The study shows that more attention should be given to the search capabilities through ongoing training and awareness in order to maximise the benefit from the available resources and tools. Originality/value: The hypothetical value of the federated search tools has not been previously examined and analysed to understand user trends.

The HTML title tag information should identify and describe exactly what a Web page contains. This paper analyzes the "Title element" and raises a significant question: "Why is the title tag important?" Search engines base search results and page rankings on certain criteria. Among the most important criteria is the presence of the search keywords in the title tag. This research concentrates on exploring the retrieval results of Google in retrieving Web pages without the title tag. More than one million of academic Web pages are found to be untitled, that is, they have not used the title tag.

This paper examines the problems involved in subject retrieval from full-text databases of secondary materials in the humanities. Ten such databases were studied and their search functionality evaluated, focusing on factors such as Boolean operators, document surrogates, limiting by subject area, proximity operators, phrase searching, wildcards, weighting of search terms, limiting by type of document, controlled vocabulary indexing and ranking, and display of search results. The author suggests ways in which full-text searching might be improved, whether by enhancement of database records, by introduction of enhanced search functionality, or by the education of searchers in more effective search techniques. The conclusion is that current digitization projects are not producing databases that meet the needs of scholars. (Contains 28 notes.)