Fiana Raiber

567 total citations
31 papers, 344 citations indexed

About

Fiana Raiber is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Fiana Raiber has authored 31 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Information Systems, 19 papers in Artificial Intelligence and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Fiana Raiber's work include Information Retrieval and Search Behavior (26 papers), Topic Modeling (15 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Fiana Raiber is often cited by papers focused on Information Retrieval and Search Behavior (26 papers), Topic Modeling (15 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Fiana Raiber collaborates with scholars based in Israel, United States and Australia. Fiana Raiber's co-authors include Oren Kurland, Anna Shtok, David Carmel, Ido Guy, Moshe Tennenholtz, Shay Hummel, J. Shane Culpepper, Milad Shokouhi, Filip Radlinski and Ivan Habernal and has published in prestigious journals such as ACM Transactions on Information Systems, ACM SIGIR Forum and arXiv (Cornell University).

In The Last Decade

Fiana Raiber

30 papers receiving 331 citations

Peers

Fiana Raiber

IS

AI

CVPR

SP

MSOR

Diane Hu United States

Flavian Vasile United States

Reiner Kraft United States

Paolo Tomeo Italy

Bodo Billerbeck Australia

Yukihiro Tagami Japan

Cheng Xiang Zhai United States

Pu‐Jen Cheng Taiwan

Srinivasan H. Sengamedu United States

Jiaul H. Paik India

Diane Hu United States

Fiana Raiber

182 ×0.8

IS

164 ×0.8

AI

63 ×0.7

CVPR

27 ×0.4

SP

57 ×1.3

MSOR

Citations per year, relative to Fiana Raiber Fiana Raiber (= 1×) peers Diane Hu

Countries citing papers authored by Fiana Raiber

Since Specialization

Citations

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

Fields of papers citing papers by Fiana Raiber

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fiana Raiber

This figure shows the co-authorship network connecting the top 25 collaborators of Fiana Raiber. A scholar is included among the top collaborators of Fiana Raiber 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 Fiana Raiber. Fiana Raiber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Raiber, Fiana, et al.. (2023). Entity-Based Relevance Feedback for Document Retrieval. 177–187. 1 indexed citations

2.

Raiber, Fiana, et al.. (2022). From Cluster Ranking to Document Ranking. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2137–2141. 1 indexed citations

3.

Kurland, Oren, et al.. (2021). Driving the Herd: Search Engines as Content Influencers. arXiv (Cornell University). 586–595. 1 indexed citations

4.

Raiber, Fiana, et al.. (2021). Recommending Search Queries in Documents Using Inter N-Gram Similarities. 211–220. 1 indexed citations

5.

Raiber, Fiana, et al.. (2020). Cluster-Based Document Retrieval with Multiple Queries. 11. 33–40. 1 indexed citations

6.

Raiber, Fiana & Oren Kurland. (2019). Relevance Feedback. ACM Transactions on Information Systems. 37(4). 1–28. 4 indexed citations

7.

Shtok, Anna, et al.. (2019). Information Needs, Queries, and Query Performance Prediction. RMIT Research Repository (RMIT University Library). 395–404. 16 indexed citations

8.

Carmel, David, et al.. (2019). Enriching News Articles with Related Search Queries. 162–172. 1 indexed citations

9.

Guy, Ido, et al.. (2018). Selective Cluster Presentation on the Search Results Page. ACM Transactions on Information Systems. 36(3). 1–42. 7 indexed citations

10.

Raiber, Fiana, et al.. (2017). Information Retrieval Meets Game Theory. 465–474. 13 indexed citations

11.

Raiber, Fiana, et al.. (2016). Selective Cluster-Based Document Retrieval. 10. 1473–1482. 8 indexed citations

12.

Habernal, Ivan, Fiana Raiber, Anna Shtok, et al.. (2016). New Collection Announcement. TUbilio (Technical University of Darmstadt). 701–704. 5 indexed citations

13.

Raiber, Fiana, Oren Kurland, Filip Radlinski, & Milad Shokouhi. (2015). Learning Asymmetric Co-Relevance. 281–290. 7 indexed citations

14.

Raiber, Fiana, et al.. (2014). The search duel. 919–922. 3 indexed citations

15.

Raiber, Fiana & Oren Kurland. (2014). The correlation between cluster hypothesis tests and the effectiveness of cluster-based retrieval. 1155–1158. 5 indexed citations

16.

Raiber, Fiana & Oren Kurland. (2013). The Technion at TREC 2013 Web Track: Cluster-based Document Retrieval. Text REtrieval Conference. 2 indexed citations

17.

Raiber, Fiana, Kevyn Collins‐Thompson, & Oren Kurland. (2013). Shame to be sham. 1013–1016. 1 indexed citations

18.

Kurland, Oren, et al.. (2012). Back to the roots. 823–832. 21 indexed citations

19.

Hummel, Shay, Anna Shtok, Fiana Raiber, Oren Kurland, & David Carmel. (2012). Clarity re-visited. 1039–1040. 3 indexed citations

20.

Raiber, Fiana & Oren Kurland. (2010). On identifying representative relevant documents. 99–108. 11 indexed citations

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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