Eugene Agichtein

10.8k citations
141 papers · 7.1k indexed · 5 hit papers · h-index 39

Impact in

    • Mobile Crowdsensing and Crowdsourcing
    • Expert finding and Q&A systems
    • Web Data Mining and Analysis
    • Information Retrieval and Search Behavior
    • Recommender Systems and Techniques

Papers in

    • Mobile Crowdsensing and Crowdsourcing 29
    • Expert finding and Q&A systems 44
    • Information Retrieval and Search Behavior 44
    • Web Data Mining and Analysis 32
    • Recommender Systems and Techniques 13

Eugene Agichtein

136 papers receiving 6.5k citations

Hit Papers

Proceedings of the 26th International Conference on World Wide Web Companion 2017 · 269 citations
2692000202620082017250500750

Peers

Eugene Agichtein
Comparison fields: 5 of 142
  • Computer Science Applications 1.3k
  • Information Systems 4.1k
  • Artificial Intelligence 4.2k
  • Communication 464
  • Information Systems and Management 340
Replace F. Maxwell Harper with:
F. Maxwell Harper United States
Peter Brusilovsky United States
Nicholas J. Belkin United States
Eytan Adar United States
Margaret‐Anne Storey Canada
Daniel S. Weld United States
Iryna Gurevych Germany
Mark Sanderson Australia
Nick Craswell United States
Christian Bird United States
Eugene Agichtein relative to F. Maxwell Harper United States F. Maxwell Harper's profile →
Citations per field
00.5×2.7×
F. Maxwell Harper · 1×
Citations per year

Countries citing papers authored by Eugene Agichtein

Since Specialization
Citations

This map shows the geographic impact of Eugene Agichtein's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eugene Agichtein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eugene Agichtein more than expected).

Fields of papers citing papers by Eugene Agichtein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eugene Agichtein. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eugene Agichtein. The network helps show where Eugene Agichtein may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Eugene Agichtein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eugene Agichtein Line = papers co-authored together Eugene Agichtein links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20241
4
Proceedings of the 26th International Conference on World Wide Web Companion
Hit paper breakdown →
2017269
5
Overview of the Medical Question Answering Task at TREC 2017 LiveQA.
201720
6
Emory University at TREC LiveQA 2016: Combining Crowdsourcing and Learning-To-Rank Approaches for Real-Time Complex Question Answering.
20161
7
Overview of the TREC 2015 LiveQA Track.
201522
8
Proceedings of the fifth ACM international conference on Web search and data mining
20126
9
Query Ambiguity Revisited: Clickthrough Measures for Distinguishing Informational and Ambiguous Queries
201013
10
Towards Automatic Question Answering over Social Media by Learning Question Equivalence Patterns
20100
11
The ``Nays'' Have It: Exploring Effects of Sentiment in Collaborative Knowledge Sharing
20102
12
THE SOCIAL FUTURE OF WEB SEARCH: MODELING, EXPLOITING, AND SEARCHING COLLABORATIVELY GENERATED CONTENT
20097
13
Combining Lexical, Syntactic, and Semantic Evidence For Textual Entailment Classification
200811
14
Domain Ontology Construction from Biomedical Text.
20074
15
Confidence Estimation Methods for Partially Supervised Information Extraction.
200611
16
Improving Web Search Ranking by Incorporating User Behavior
200649
17
Web Information Extraction and User Modeling: Towards Closing the Gap.
20064
18
Factoid Question Answering over Unstructured and Structured Web Content.
200527
19
Scaling Information Extraction to Large Document Collections.
200521
20
Exploiting diverse knowledge sources via maximum entropy in named entity recognition
1998138

About Eugene Agichtein

Eugene Agichtein is a scholar working on Computer Science Applications, Information Systems, Artificial Intelligence, Signal Processing and Human-Computer Interaction, having authored 141 papers that have together received 7.1k indexed citations. Recurring topics across this work include Topic Modeling (60 papers), Expert finding and Q&A systems (44 papers), Information Retrieval and Search Behavior (44 papers), Web Data Mining and Analysis (32 papers), Mobile Crowdsensing and Crowdsourcing (29 papers), Natural Language Processing Techniques (23 papers), Recommender Systems and Techniques (13 papers) and Advanced Text Analysis Techniques (11 papers). The work is most often cited by research in Computer Science Applications (1.3k citations), Information Systems (4.1k citations), Artificial Intelligence (4.2k citations), Communication (464 citations) and Information Systems and Management (340 citations). Eugene Agichtein has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Luis Gravano, Susan Dumais, Eric Brill, Qi Guo, Yandong Liu, Carlos Castillo, Debora Donato, Gilad Mishne, Aristides Gionis and Jiang Bian. Their work appears in journals such as ACM SIGIR Forum, ACM Transactions on Knowledge Discovery from Data, Information Retrieval, Bioinformatics and ACM Transactions on Database Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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