Idan Szpektor

58 papers receiving 1.3k citations

Peers

Idan Szpektor
Comparison fields: 5 of 70
  • Artificial Intelligence 1.3k
  • Information Systems 514
  • Computer Science Applications 184
  • Computer Vision and Pattern Recognition 116
  • Molecular Biology 79
Replace Shourya Roy with:
Shourya Roy India
Udo Kruschwitz United Kingdom
Ahmad A. Kardan Iran
Stefano Faralli Italy
Naama Zwerdling Israel
Yiu‐Kai Ng United States
Nicola Ferro Italy
Vibhu O. Mittal United States
Debasis Ganguly Ireland
Daniel E. Rose United States
Idan Szpektor relative to Shourya Roy India Shourya Roy's profile →
Citations per field
00.5×3.4×
Shourya Roy · 1×
Citations per year

Countries citing papers authored by Idan Szpektor

Since Specialization
Citations

This map shows the geographic impact of Idan Szpektor'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 Idan Szpektor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Idan Szpektor more than expected).

Fields of papers citing papers by Idan Szpektor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Idan Szpektor. 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 Idan Szpektor. The network helps show where Idan Szpektor may publish in the future.

Co-authorship network of co-authors of Idan Szpektor

This figure shows the co-authorship network connecting the top 25 collaborators of Idan Szpektor. A scholar is included among the top collaborators of Idan Szpektor based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Idan Szpektor. Idan Szpektor is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 3
4 1
5 4
6 12
7 4
8 25
9
Generating Synthetic Comparable Questions for News Articles
2
10
A Two Level Model for Context Sensitive Inference Rules
15
11
Using Lexical Expansion to Learn Inference Rules from Sparse Data
3
12
Learning Verb Inference Rules from Linguistically-Motivated Evidence
14
13
Generating Entailment Rules from FrameNet
39
14
Addressing Discourse and Document Structure in the RTE Search Task.
11
15
Contextual Preferences
31
16
Efficient Semantic Deduction and Approximate Matching over Compact Parse Forests.
23
17
Instance-based Evaluation of Entailment Rule Acquisition
49
18
Cross Lingual and Semantic Retrieval for Cultural Heritage Appreciation
4
19
Investigating a Generic Paraphrase-Based Approach for Relation Extraction
67
20
Scaling Web-based Acquisition of Entailment Relations.
118

About Idan Szpektor

Idan Szpektor is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems, having authored 61 papers that have together received 1.5k indexed citations. Recurring topics across this work include Topic Modeling (45 papers), Natural Language Processing Techniques (39 papers) and Expert finding and Q&A systems (10 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computer Science Applications (184 citations) and Information Systems (514 citations). Idan Szpektor has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Ido Dagan, Yoelle Maarek, Gideon Dror, Dan Pelleg, Lili Kotlerman, Maayan Zhitomirsky‐Geffet, Bonaventura Coppola, Hristo Tanev, Roy Bar-Haim and Oleg Rokhlenko. Their work appears in journals such as BMC Medical Informatics and Decision Making, Transactions of the Association for Computational Linguistics and Natural Language Engineering.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026