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118 results on '"De Roeck, Anne"'

2. Optimization of an Integrated Model for Automatic Reduction and Expansion of Long Queries

Author

Song, Dawei, Shi, Yanjie, Zhang, Peng, Hou, Yuexian, Hu, Bin, Jia, Yuan, Huang, Qiang, Kruschwitz, Udo, De Roeck, Anne, Bruza, Peter, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Banchs, Rafael E., editor, Silvestri, Fabrizio, editor, Liu, Tie-Yan, editor, Zhang, Min, editor, Gao, Sheng, editor, and Lang, Jun, editor

Published
2013
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3. Using Dempster-Shafer’s Evidence Theory for Query Expansion Based on Freebase Knowledge

Author

Pan, Dazhao, Zhang, Peng, Li, Jingfei, Song, Dawei, Wen, Ji-Rong, Hou, Yuexian, Hu, Bin, Jia, Yuan, De Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Banchs, Rafael E., editor, Silvestri, Fabrizio, editor, Liu, Tie-Yan, editor, Zhang, Min, editor, Gao, Sheng, editor, and Lang, Jun, editor

Published
2013
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4. Analysis of Query Reformulations in a Search Engine of a Local Web Site

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Nanas, Nikolaos, Adeyanju, Ibrahim, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Baeza-Yates, Ricardo, editor, de Vries, Arjen P., editor, Zaragoza, Hugo, editor, Cambazoglu, B. Barla, editor, Murdock, Vanessa, editor, Lempel, Ronny, editor, and Silvestri, Fabrizio, editor

Published
2012
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5. Enriching Query Flow Graphs with Click Information

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Adeyanju, Ibrahim, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Salem, Mohamed Vall Mohamed, editor, Shaalan, Khaled, editor, Oroumchian, Farhad, editor, Shakery, Azadeh, editor, and Khelalfa, Halim, editor

Published
2011
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6. Exploring Ant Colony Optimisation for Adaptive Interactive Search

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Nanas, Nikolaos, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Amati, Giambattista, editor, and Crestani, Fabio, editor

Published
2011
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7. Moving towards Adaptive Search in Digital Libraries

Author

Kruschwitz, Udo, Albakour, M-Dyaa, Niu, Jinzhong, Leveling, Johannes, Nanas, Nikolaos, Kim, Yunhyong, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Bernardi, Raffaella, editor, Chambers, Sally, editor, Gottfried, Björn, editor, Segond, Frédérique, editor, and Zaihrayeu, Ilya, editor

Published
2011
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8. AutoEval: An Evaluation Methodology for Evaluating Query Suggestions Using Query Logs

Author

Albakour, M-Dyaa, Kruschwitz, Udo, Nanas, Nikolaos, Kim, Yunhyong, Song, Dawei, Fasli, Maria, De Roeck, Anne, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Clough, Paul, editor, Foley, Colum, editor, Gurrin, Cathal, editor, Jones, Gareth J. F., editor, Kraaij, Wessel, editor, Lee, Hyowon, editor, and Mudoch, Vanessa, editor

Published
2011
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9. Overcoming Schema Heterogeneity between Linked Semantic Repositories to Improve Coreference Resolution

Author

Nikolov, Andriy, Uren, Victoria, Motta, Enrico, de Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gómez-Pérez, Asunción, editor, Yu, Yong, editor, and Ding, Ying, editor

Published
2009
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10. What Happened to Content-Based Information Filtering?

Author

Nanas, Nikolaos, De Roeck, Anne, Vavalis, Manolis, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Azzopardi, Leif, editor, Kazai, Gabriella, editor, Robertson, Stephen, editor, Rüger, Stefan, editor, Shokouhi, Milad, editor, Song, Dawei, editor, and Yilmaz, Emine, editor

Published
2009
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11. Using the Dempster-Shafer Theory of Evidence to Resolve ABox Inconsistencies

Author

Nikolov, Andriy, Uren, Victoria, Motta, Enrico, de Roeck, Anne, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, da Costa, Paulo Cesar G., editor, d’Amato, Claudia, editor, Fanizzi, Nicola, editor, Laskey, Kathryn B., editor, Laskey, Kenneth J., editor, Lukasiewicz, Thomas, editor, Nickles, Matthias, editor, and Pool, Michael, editor

Published
2008
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12. Refining Instance Coreferencing Results Using Belief Propagation

Author

Nikolov, Andriy, Uren, Victoria, Motta, Enrico, de Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Domingue, John, editor, and Anutariya, Chutiporn, editor

Published
2008
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14. Multimodal Dynamic Optimization: From Evolutionary Algorithms to Artificial Immune Systems

Author

Nanas, Nikolaos, De Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, de Castro, Leandro Nunes, editor, Von Zuben, Fernando José, editor, and Knidel, Helder, editor

Published
2007
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15. Immune-Inspired Adaptive Information Filtering

Author

Nanas, Nikolaos, de Roeck, Anne, Uren, Victoria, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bersini, Hugues, editor, and Carneiro, Jorge, editor

Published
2006
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16. Nootropia: A User Profiling Model Based on a Self-Organising Term Network

Author

Nanas, Nikolaos, Uren, Victoria S., de Roeck, Anne, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Nicosia, Giuseppe, editor, Cutello, Vincenzo, editor, Bentley, Peter J., editor, and Timmis, Jon, editor

Published
2004
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17. Multi-topic Information Filtering with a Single User Profile

Author

Nanas, Nikolaos, Uren, Victoria, de Roeck, Anne, Domingue, John, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Vouros, George A., editor, and Panayiotopoulos, Themistoklis, editor

Published
2004
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18. Extracting Semistructured Data - Lessons Learnt

Author

Kruschwitz, Udo, De Roeck, Anne, Scott, Paul, Steel, Sam, Turner, Ray, Webb, Nick, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, and Christodoulakis, Dimitris N., editor

Published
2000
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19. The YPA – An Assistant for Classified Directory Enquiries

Author

De Roeck, Anne, Kruschwitz, Udo, Scott, Paul, Steel, Sam, Turner, Ray, Webb, Nick, Goos, Gerhard, editor, Hartmanis, Juris, editor, van Leeuwen, Jan, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Azvine, Benham, editor, Nauck, Detlef D., editor, and Azarmi, Nader, editor

Published
2000
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29. Moving towards Adaptive Search in Digital Libraries

Author

Kruschwitz, Udo, primary, Albakour, M-Dyaa, additional, Niu, Jinzhong, additional, Leveling, Johannes, additional, Nanas, Nikolaos, additional, Kim, Yunhyong, additional, Song, Dawei, additional, Fasli, Maria, additional, and De Roeck, Anne, additional

Published
2011
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40. ComTax: community-driven curation for taxonomic databases

Author

Morse, David, Yang, Hui, Willis, Alistair, De Roeck, Anne, and King, David

Abstract

This poster presents the work of the ComTax project to develop a community-driven curation process among practicing scientists and citizen scientists. The project provides tools to help scientists identify and validate appropriate taxonomic names from the scanned historical literature. The system operates on scanned documents, typically taken from the Biodiversity Heritage Library, although documents sourced from other repositories could be used.\ud \ud The system is intended to be used on uncorrected text after optical character recognition (OCR) on the scanned images. The key stages are:\ud \ud 1. Identify possible taxonomic names in the scanned text using machine learning techniques.\ud \ud 2. Verify the extracted names against existing databases. If present, the source scanned text can be automatically marked-up with the name.\ud \ud 3. Unverified names might mean they are not currently recorded in the verification databases, typically because the old name in the literature has been reclassified, or because erroneous OCR means that the name is incorrectly transcribed in the scanned text. In either case:\ud \ud 3.1. Present the proposed name to domain experts or citizen scientists for validation or correction, potentially through a voting mechanism to collect expert judgments on the putative taxonomic name.\ud \ud 3.2. Mark-up the scanned text with the corrected spelling of the name and offer validated taxonomic names for further use by the community.\ud \ud This poster will describe the technical challenges facing the ComTax project, and highlight potential extensions of the work to the curation of other entities of interest in the legacy literature or of different disciplines.

Published
2013

41. Literature-driven Curation for Taxonomic Name Databases

Author

Yang, Hui, Willis, Alistair, Morse, David, and De Roeck, Anne

Abstract

Digitized biodiversity literature provides a wealth of content for using biodiversity knowledge by machines. However, identifying taxonomic names and the associated semantic metadata is a difficult and labour intensive process. We present a system to support human assisted creation of semantic metadata. Information extraction techniques auto-matically identify taxonomic names from scanned documents. They are then presented to users for manual correction or verification. The tools that support the curation process include taxonomic name identification and mapping, and community-driven taxonomic name verification. Our research shows the potential for these information extrac-tion techniques to support research and curation in disciplines dependent upon scanned documents

Published
2013

42. Curation tools for taxonomic databases

Author

Morse, David, De Roeck, Anne, Willis, Alistair, and Yang, Hui

Abstract

Biological taxonomy is the classification of living and fossil organisms. Taxonomists have identified and named some 1.8 million species of animals, plants, and microorganisms, a fraction of Earth's estimated 5‐30 million species. Part of the effort of taxonomy lies in developing and curating taxonomic databases, which support access to the taxonomy literature, and provide basic knowledge needed for management and conservation of biodiversity.\ud \ud A major difficulty facing this task is incorporating knowledge that is currently contained only in the historical literature. Extracting this knowledge is a difficult and labour‐intensive process, as scanning errors and other variations in nomenclature mean that particular names must be manually verified as part of the process. For example, Actinobacillus actionomy, Actinobacillus actionomyce, and Actinobacillus actionomycetam could all be variants of the same name. ComTax is an ongoing project to develop a community‐driven curation process among taxonomists, by providing tools to help them identify and validate taxonomic names from the scanned historical literature. The system operates on scanned documents following optical character recognition (OCR). The key stages are:\ud \ud 1. Identify possible taxonomic names from scanned text. Names might be new either because they do not appear in existing databases, or because they have been incorrectly identified by OCR.\ud \ud 2. Present the proposed name to a domain expert for validation or correction.\ud \ud 3. Present validated taxonomic names for curation. Organizations like Global Biodiversity Information Facility (GBIF) manage the curation of taxonomic databases. This poster describes the technical challenges facing the ComTax project, and will discuss our work with the Natural History Museum to integrate the curation process into taxonomists' workflow. We also demonstrate the relevance of this work within the wider context of biological taxonomy curation.

Published
2013

43. Speculative requirements: automatic detection of uncertainty in natural language requirement

Author

Yang, Hui, De Roeck, Anne, Gervasi, Vincenzo, Willis, Alistair, Nuseibeh, Bashar, EPSRC, SFI, and ERC

Subjects
speculative requirements, machine learning, uncertainty scopes, natural language requirements, rule-based approach, uncertainty cues, uncertainty
Abstract

peer-reviewed Stakeholders frequently use speculative language when they need to convey their requirements with some degree of uncertainty. Due to the intrinsic vagueness of speculative language, speculative requirements risk being misunderstood, and related uncertainty overlooked, and may benefit from careful treatment in the requirements engineering process. In this paper, we present a linguistically-oriented approach to automatic detection of uncertainty in natural language (NL) requirements. Our approach comprises two stages. First we identify speculative sentences by applying a machine learning algorithm called Conditional Random Fields (CRFs) to identify uncertainty cues. The algorithm exploits a rich set of lexical and syntactic features extracted from requirements sentences. Second, we try to determine the scope of uncertainty. We use a rule-based approach that draws on a set of hand-crafted linguistic heuristics to determine the uncertainty scope with the help of dependency structures present in the sentence parse tree. We report on a series of experiments we conducted to evaluate the performance and usefulness of our system.

Published
2012

44. Moving towards adaptive search

Author

Dignum, Stephen, Kim, Yunhyong, Kruschwitz, Udo, Song, Dawei, Fasli, Maria, and De Roeck, Anne

Abstract

Information retrieval has become very popular over the last\ud decade with the advent of the Web. Nevertheless, searching on the Web is very different to searching on smaller, often more structured collections such as intranets and digital libraries. Such collections are the focus of the AutoAdapt project. The project seeks to aid user search by providing well structured domain knowledge to assist query modification and navigation.\ud \ud There are two challenges: acquiring the domain knowledge and adapting it automatically to the specific interest of the user community. The paper introduces an implemented prototype that serves as a starting point on the\ud way to truly adaptive search.

Published
2009

46. Using domain models for context-rich user logging

Author

Dignum, Stephen, Kim, Yunhyong, Kruschwitz, Udo, Song, Dawei, Fasli, Maria, and De Roeck, Anne

Abstract

This paper describes the prototype interactive search system being developed within the AutoAdapt project1. The AutoAdapt project seeks to enhance the user experience in searching for information and navigating within selected domain collections by providing structured representations of domain knowledge to be directly explored, logged, adapted and updated to reflect user needs. We propose that this structure is a valuable stepping-stone in context-rich logging of user activities within the information seeking environment. Here we describe the primary components that have been implemented and the user interactions that it will support.

Published
2009

47. Detecting dangerous coordination ambiguities using word distribution

Author

Chantree, Francis, Willis, Alistair, Kilgarriff, Adam, De Roeck, Anne, Nicolov, Nicolas, Bontcheva, Kalina, Anjelova, Galia, and Mitkov, Ruslan

Abstract

In this paper we present heuristics for resolving coordination ambiguities. We test the hypothesis that the most likely reading of a coordination can be predicted using word distribution information from a generic corpus. Our heuristics are based upon the relative frequency of the coordination in the corpus, the distributional similarity of the coordinated words, and the collocation frequency between the coordinated words and their modifiers. These heuristics have varying but useful predictive power. They also take into account our view that many ambiguities cannot be effectively disambiguated, since human perceptions vary widely.

Published
2007

48. Measuring improvement in latent semantic analysis-based marking systems: using a computer to mark questions about HTML

Author

Haley, Debra, Thomas, Pete, De Roeck, Anne, and Petre, Marian

Abstract

This paper proposes two unconventional metrics as animportant tool for assessment research: the Manhattan(L1) and the Euclidean (L2) distance measures. We used them to evaluate the results of a Latent Semantic Analysis(LSA) system to assess short answers to two questionsabout HTML in an introductory computer science class.This is the only study, as far as we know, that addresses the question of how well an LSA-based system can evaluate answers in the very specific and technical language of HTML. We found that, although there are several ways to measure automatic assessment results in the literature, they were not useful for our purposes. We want to compare the marks given by LSA to marks awarded by a human tutor. We demonstrate how L1 and L2 quantify the results of varying the amount of training data necessary to enable LSA to mark the answers to two HTML questions. Although this paper describes the use of the metrics in one particular case, it has more general applicability. Much fine-tuning of an LSA marking system is required for good results. A researcher needs an easy way to evaluate the results of various modifications to the system. The Manhattan and the Euclidean distance measures provide this functionality.

Published
2007

49. Optimization of an integrated model for automatic reduction and expansion of long queries

Author

Liu, T Y, Gao, S, Lang, J, Zhang, M, Banchs, R, Silvestri, F, Song, Dawei, Shi, Yanjie, Zhang, Peng, Hou, Yuexian, Hu, Bin, Jia, Yuan, Huang, Qiang, Kruschwitz, Udo, de Roeck, Anne, Bruza, Peter, Liu, T Y, Gao, S, Lang, J, Zhang, M, Banchs, R, Silvestri, F, Song, Dawei, Shi, Yanjie, Zhang, Peng, Hou, Yuexian, Hu, Bin, Jia, Yuan, Huang, Qiang, Kruschwitz, Udo, de Roeck, Anne, and Bruza, Peter

Abstract

A long query provides more useful hints for searching relevant documents, but it is likely to introduce noise which affects retrieval performance. In order to smooth such adverse effect, it is important to reduce noisy terms, introduce and boost additional relevant terms. This paper presents a comprehensive framework, called Aspect Hidden Markov Model (AHMM), which integrates query reduction and expansion, for retrieval with long queries. It optimizes the probability distribution of query terms by utilizing intra-query term dependencies as well as the relationships between query terms and words observed in relevance feedback documents. Empirical evaluation on three large-scale TREC collections demonstrates that our approach, which is automatic, achieves salient improvements over various strong baselines, and also reaches a comparable performance to a state of the art method based on user’s interactive query term reduction and expansion.

Published
2013

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