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1. Reviewer assignment problem: A scoping review

Author

Jovanovic, Jelena and Bagheri, Ebrahim

Subjects
Computer Science - Information Retrieval, Computer Science - Digital Libraries, Computer Science - Machine Learning, H.3.3, I.2.7, H.4.m
Abstract

Peer review is an integral component of scientific research. The quality of peer review, and consequently the published research, depends to a large extent on the ability to recruit adequate reviewers for submitted papers. However, finding such reviewers is an increasingly difficult task due to several factors, such as the continuous increase both in the production of scientific papers and the workload of scholars. To mitigate these challenges, solutions for automated association of papers with "well matching" reviewers - the task often referred to as reviewer assignment problem (RAP) - have been the subject of research for thirty years now. Even though numerous solutions have been suggested, to our knowledge, a recent systematic synthesis of the RAP-related literature is missing. To fill this gap and support further RAP-related research, in this paper, we present a scoping review of computational approaches for addressing RAP. Following the latest methodological guidance for scoping reviews, we have collected recent literature on RAP from three databases (Scopus, Google Scholar, DBLP) and, after applying the eligibility criteria, retained 26 studies for extracting and synthesising data on several aspects of RAP research including: i) the overall framing of and approach to RAP; ii) the criteria for reviewer selection; iii) the modelling of candidate reviewers and submissions; iv) the computational methods for matching reviewers and submissions; and v) the methods for evaluating the performance of the proposed solutions. The paper summarises and discusses the findings for each of the aforementioned aspects of RAP research and suggests future research directions., Comment: 27 pages with 2 figures

Published
2023

2. Query Performance Prediction: From Fundamentals to Advanced Techniques

Author

Arabzadeh, Negar, Meng, Chuan, Aliannejadi, Mohammad, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Goharian, Nazli, editor, Tonellotto, Nicola, editor, He, Yulan, editor, Lipani, Aldo, editor, McDonald, Graham, editor, Macdonald, Craig, editor, and Ounis, Iadh, editor

Published
2024
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3. LaQuE: Enabling Entity Search at Scale

Author

Arabzadeh, Negar, Bigdeli, Amin, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Goharian, Nazli, editor, Tonellotto, Nicola, editor, He, Yulan, editor, Lipani, Aldo, editor, McDonald, Graham, editor, Macdonald, Craig, editor, and Ounis, Iadh, editor

Published
2024
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4. Learning to Jointly Transform and Rank Difficult Queries

Author

Bigdeli, Amin, Arabzadeh, Negar, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Goharian, Nazli, editor, Tonellotto, Nicola, editor, He, Yulan, editor, Lipani, Aldo, editor, McDonald, Graham, editor, Macdonald, Craig, editor, and Ounis, Iadh, editor

Published
2024
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5. Context-Aware Query Term Difficulty Estimation for Performance Prediction

Author

Saleminezhad, Abbas, Arabzadeh, Negar, Beheshti, Soosan, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Goharian, Nazli, editor, Tonellotto, Nicola, editor, He, Yulan, editor, Lipani, Aldo, editor, McDonald, Graham, editor, Macdonald, Craig, editor, and Ounis, Iadh, editor

Published
2024
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6. Estimating Query Performance Through Rich Contextualized Query Representations

Author

Ebrahimi, Sajad, Khodabakhsh, Maryam, Arabzadeh, Negar, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Goharian, Nazli, editor, Tonellotto, Nicola, editor, He, Yulan, editor, Lipani, Aldo, editor, McDonald, Graham, editor, Macdonald, Craig, editor, and Ounis, Iadh, editor

Published
2024
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8. Early Maladaptive Schemas, Cognitive Fusion, and Anabolic-Androgenic Steroid Use Attitudes: The Mediating Role of Muscle Dysmorphia in Iran.

Author

Ebrahimi, Mehdi, Zamani, Zahra, and Bagheri, Ebrahim

Subjects
SUBSTANCE abuse prevention, MUSCLE dysmorphia, BODY schema, PHYSICAL fitness centers, COGNITIVE training, BODY image
Abstract

In recent decades, the interest in having an ideal body in men has caused a pathological tendency to be muscular, followed by a tendency to use anabolic-androgenic steroids (AASs). This study was designed to evaluate the mediating role of muscle dysmorphia in the relationship between early maladaptive schemas and body image-related cognitive fusion with the tendency to use AAS in male athletes. Out of the total number of men referring to fitness clubs in Isfahan, Iran, 474 men were evaluated using a multistage random cluster sampling method. The questionnaires used in this research included the Muscle Dysmorphic Disorder Inventory, Cognitive Fusion Questionnaire—Body Image, Young Schema Questionnaire—Short Form, and Prototype Willingness Model Questionnaire. The results demonstrated that the relationship of AAS use with body image-related cognitive fusion and the three maladaptive schemas with the mediation of muscle dysmorphia is significant. The present study provides significant implications in the discussion of prevention and treatment of AAS addiction. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Understanding and Mitigating Gender Bias in Information Retrieval Systems

Author

Bigdeli, Amin, Arabzadeh, Negar, Seyedsalehi, Shirin, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kamps, Jaap, editor, Goeuriot, Lorraine, editor, Crestani, Fabio, editor, Maistro, Maria, editor, Joho, Hideo, editor, Davis, Brian, editor, Gurrin, Cathal, editor, Kruschwitz, Udo, editor, and Caputo, Annalina, editor

Published
2023
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11. Neural Ad-Hoc Retrieval Meets Open Information Extraction

Author

Vo, Duc-Thuan, Zarrinkalam, Fattane, Pham, Ba, Arabzadeh, Negar, Salamat, Sara, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kamps, Jaap, editor, Goeuriot, Lorraine, editor, Crestani, Fabio, editor, Maistro, Maria, editor, Joho, Hideo, editor, Davis, Brian, editor, Gurrin, Cathal, editor, Kruschwitz, Udo, editor, and Caputo, Annalina, editor

Published
2023
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12. Learning Query-Space Document Representations for High-Recall Retrieval

Author

Salamat, Sara, Arabzadeh, Negar, Zarrinkalam, Fattane, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kamps, Jaap, editor, Goeuriot, Lorraine, editor, Crestani, Fabio, editor, Maistro, Maria, editor, Joho, Hideo, editor, Davis, Brian, editor, Gurrin, Cathal, editor, Kruschwitz, Udo, editor, and Caputo, Annalina, editor

Published
2023
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13. Don’t Raise Your Voice, Improve Your Argument: Learning to Retrieve Convincing Arguments

Author

Salamat, Sara, Arabzadeh, Negar, Bigdeli, Amin, Seyedsalehi, Shirin, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kamps, Jaap, editor, Goeuriot, Lorraine, editor, Crestani, Fabio, editor, Maistro, Maria, editor, Joho, Hideo, editor, Davis, Brian, editor, Gurrin, Cathal, editor, Kruschwitz, Udo, editor, and Caputo, Annalina, editor

Published
2023
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14. De-biasing Relevance Judgements for Fair Ranking

Author

Bigdeli, Amin, Arabzadeh, Negar, Seyedsalehi, Shirin, Mitra, Bhaskar, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kamps, Jaap, editor, Goeuriot, Lorraine, editor, Crestani, Fabio, editor, Maistro, Maria, editor, Joho, Hideo, editor, Davis, Brian, editor, Gurrin, Cathal, editor, Kruschwitz, Udo, editor, and Caputo, Annalina, editor

Published
2023
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15. A metric Suite for Systematic Quality Assessment of Linked Open Data

Author

Behkamal, Behshid, Kahani, Moshen, Bagheri, Ebrahim, and Sazvar, Majid

Subjects
Computer Science - Databases, 97R50, E.0, E.1
Abstract

Abstract- The vision of the Linked Open Data (LOD) initiative is to provide a distributed model for publishing and meaningfully interlinking open data. The realization of this goal depends strongly on the quality of the data that is published as a part of the LOD. This paper focuses on the systematic quality assessment of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics. This will help publishers to filter out low-quality data based on the quality assessment results, which in turn enables data consumers to make better and more informed decisions when using the open datasets., Comment: 20 pages, 12 tables

Published
2020

20. A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers

Author

Bigdeli, Amin, Arabzadeh, Negar, Seyedsalehi, Shirin, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hagen, Matthias, editor, Verberne, Suzan, editor, Macdonald, Craig, editor, Seifert, Christin, editor, Balog, Krisztian, editor, Nørvåg, Kjetil, editor, and Setty, Vinay, editor

Published
2022
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25. An Extensible Toolkit of Query Refinement Methods and Gold Standard Dataset Generation

Author

Fani, Hossein, Tamannaee, Mahtab, Zarrinkalam, Fattane, Samouh, Jamil, Paydar, Samad, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hiemstra, Djoerd, editor, Moens, Marie-Francine, editor, Mothe, Josiane, editor, Perego, Raffaele, editor, Potthast, Martin, editor, and Sebastiani, Fabrizio, editor

Published
2021
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26. Query Performance Prediction Through Retrieval Coherency

Author

Arabzadeh, Negar, Bigdeli, Amin, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hiemstra, Djoerd, editor, Moens, Marie-Francine, editor, Mothe, Josiane, editor, Perego, Raffaele, editor, Potthast, Martin, editor, and Sebastiani, Fabrizio, editor

Published
2021
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27. Exploring Gender Biases in Information Retrieval Relevance Judgement Datasets

Author

Bigdeli, Amin, Arabzadeh, Negar, Zihayat, Morteza, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hiemstra, Djoerd, editor, Moens, Marie-Francine, editor, Mothe, Josiane, editor, Perego, Raffaele, editor, Potthast, Martin, editor, and Sebastiani, Fabrizio, editor

Published
2021
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28. Can artificial intelligence help decision makers navigate the growing body of systematic review evidence? A cross-sectional survey

Author

Lunny, Carole, primary, Whitelaw, Sera, additional, Reid, Emma K, additional, Chi, Yuan, additional, Zhang, Jia He, additional, Ferri, Nicola, additional, Kanji, Salmaan, additional, Pieper, Dawid, additional, Shea, Beverley, additional, Dourka, Jasmeen, additional, Veroniki, Areti Angeliki, additional, Arden, Clare L, additional, Pham, Ba', additional, Bagheri, Ebrahim, additional, and Tricco, Andrea C, additional

Published
2024
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30. The Impact of Foursquare Checkins on Users’ Emotions on Twitter

Author

Mirlohi Falavarjani, Seyed Amin, Hosseini, Hawre, Bagheri, Ebrahim, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Boratto, Ludovico, editor, Faralli, Stefano, editor, Marras, Mirko, editor, and Stilo, Giovanni, editor

Published
2020
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31. From Explicit to Implicit Entity Linking: A Learn to Rank Framework

Author

Hosseini, Hawre, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Goutte, Cyril, editor, and Zhu, Xiaodan, editor

Published
2020
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32. Neural Embedding-Based Metrics for Pre-retrieval Query Performance Prediction

Author

Arabzadeh, Negar, Zarrinkalam, Fattane, Jovanovic, Jelena, Bagheri, Ebrahim, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jose, Joemon M., editor, Yilmaz, Emine, editor, Magalhães, João, editor, Castells, Pablo, editor, Ferro, Nicola, editor, Silva, Mário J., editor, and Martins, Flávio, editor

Published
2020
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33. A Latent Model for Ad Hoc Table Retrieval

Author

Bagheri, Ebrahim, Al-Obeidat, Feras, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jose, Joemon M., editor, Yilmaz, Emine, editor, Magalhães, João, editor, Castells, Pablo, editor, Ferro, Nicola, editor, Silva, Mário J., editor, and Martins, Flávio, editor

Published
2020
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34. Temporal Latent Space Modeling for Community Prediction

Author

Fani, Hossein, Bagheri, Ebrahim, Du, Weichang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jose, Joemon M., editor, Yilmaz, Emine, editor, Magalhães, João, editor, Castells, Pablo, editor, Ferro, Nicola, editor, Silva, Mário J., editor, and Martins, Flávio, editor

Published
2020
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35. Open Information Extraction

Author

Vo, Duc-Thuan and Bagheri, Ebrahim

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Open Information Extraction (Open IE) systems aim to obtain relation tuples with highly scalable extraction in portable across domain by identifying a variety of relation phrases and their arguments in arbitrary sentences. The first generation of Open IE learns linear chain models based on unlexicalized features such as Part-of-Speech (POS) or shallow tags to label the intermediate words between pair of potential arguments for identifying extractable relations. Open IE currently is developed in the second generation that is able to extract instances of the most frequently observed relation types such as Verb, Noun and Prep, Verb and Prep, and Infinitive with deep linguistic analysis. They expose simple yet principled ways in which verbs express relationships in linguistics such as verb phrase-based extraction or clause-based extraction. They obtain a significantly higher performance over previous systems in the first generation. In this paper, we describe an overview of two Open IE generations including strengths, weaknesses and application areas., Comment: This paper will appear in the Encyclopedia for Semantic Computing

Published
2016

36. Business Process Mining

Author

Pourmasoumi, Asef and Bagheri, Ebrahim

Subjects
Computer Science - Software Engineering
Abstract

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today's organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining. In this paper, we briefly introduce process mining and review some of its most important techniques. Also, we investigate some of the applications of process mining in industry and present some of the most important challenges that are faced in this area., Comment: 8 pages,6 figures

Published
2016

37. Event Identification in Social Networks

Author

Zarrinkalam, Fattane and Bagheri, Ebrahim

Subjects
Computer Science - Information Retrieval, Computer Science - Social and Information Networks
Abstract

Social networks enable users to freely communicate with each other and share their recent news, ongoing activities or views about different topics. As a result, they can be seen as a potentially viable source of information to understand the current emerging topics/events. The ability to model emerging topics is a substantial step to monitor and summarize the information originating from social sources. Applying traditional methods for event detection which are often proposed for processing large, formal and structured documents, are less effective, due to the short length, noisiness and informality of the social posts. Recent event detection techniques address these challenges by exploiting the opportunities behind abundant information available in social networks. This article provides an overview of the state of the art in event detection from social networks., Comment: It will appear in Encyclopedia with Semantic Computing to be published by World Scientific

Published
2016

38. Temporal Identification of Latent Communities on Twitter

Author

Fani, Hossein, Zarrinkalam, Fattane, Zhao, Xin, Feng, Yue, Bagheri, Ebrahim, and Du, Weichang

Subjects
Computer Science - Social and Information Networks
Abstract

User communities in social networks are usually identified by considering explicit structural social connections between users. While such communities can reveal important information about their members such as family or friendship ties and geographical proximity, they do not necessarily succeed at pulling like-minded users that share the same interests together. In this paper, we are interested in identifying communities of users that share similar topical interests over time, regardless of whether they are explicitly connected to each other on the social network. More specifically, we tackle the problem of identifying temporal topic-based communities from Twitter, i.e., communities of users who have similar temporal inclination towards the current emerging topics on Twitter. We model each topic as a collection of highly correlated semantic concepts observed in tweets and identify them by clustering the time-series based representation of each concept built based on each concept's observation frequency over time. Based on the identified emerging topics in a given time period, we utilize multivariate time series analysis to model the contributions of each user towards the identified topics, which allows us to detect latent user communities. Through our experiments on Twitter data, we demonstrate i) the effectiveness of our topic detection method to detect real world topics and ii) the effectiveness of our approach compared to well-established approaches for community detection., Comment: Submitted to WSDM 2016

Published
2015

42. Extracting Temporal Event Relations Based on Event Networks

Author

Vo, Duc-Thuan, Bagheri, Ebrahim, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Azzopardi, Leif, editor, Stein, Benno, editor, Fuhr, Norbert, editor, Mayr, Philipp, editor, Hauff, Claudia, editor, and Hiemstra, Djoerd, editor

Published
2019
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43. Relationship Prediction in Dynamic Heterogeneous Information Networks

Author

Milani Fard, Amin, Bagheri, Ebrahim, Wang, Ke, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Azzopardi, Leif, editor, Stein, Benno, editor, Fuhr, Norbert, editor, Mayr, Philipp, editor, Hauff, Claudia, editor, and Hiemstra, Djoerd, editor

Published
2019
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