Anna Shtok

902 total citations
17 papers, 446 citations indexed

About

Anna Shtok is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Anna Shtok has authored 17 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Information Systems, 11 papers in Artificial Intelligence and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Anna Shtok's work include Information Retrieval and Search Behavior (15 papers), Topic Modeling (11 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Anna Shtok is often cited by papers focused on Information Retrieval and Search Behavior (15 papers), Topic Modeling (11 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Anna Shtok collaborates with scholars based in Israel, Australia and Germany. Anna Shtok's co-authors include Oren Kurland, David Carmel, Fiana Raiber, Gideon Dror, Idan Szpektor, Yoelle Maarek, Shay Hummel, J. Shane Culpepper, Ella Rabinovich and Ivan Habernal and has published in prestigious journals such as ACM Transactions on Information Systems, RMIT Research Repository (RMIT University Library) and TUbilio (Technical University of Darmstadt).

In The Last Decade

Anna Shtok

17 papers receiving 424 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Anna Shtok Israel	10	345	307	116	74	57	17	446
Cheng Xiang Zhai United States	8	298 0.9×	241 0.8×	105 0.9×	54 0.7×	21 0.4×	15	431
Qiang Cui China	8	264 0.8×	169 0.6×	57 0.5×	38 0.5×	52 0.9×	13	343
Huizhong Duan United States	11	297 0.9×	307 1.0×	61 0.5×	24 0.3×	69 1.2×	16	402
Bodo Billerbeck Australia	9	230 0.7×	161 0.5×	67 0.6×	85 1.1×	18 0.3×	19	317
Ahu Sieg United States	8	298 0.9×	188 0.6×	69 0.6×	60 0.8×	17 0.3×	9	353
Reiner Kraft United States	9	245 0.7×	155 0.5×	57 0.5×	62 0.8×	13 0.2×	19	325
Christopher C. Vogt United States	5	206 0.6×	191 0.6×	80 0.7×	121 1.6×	12 0.2×	8	344
Wisam Dakka United States	7	179 0.5×	239 0.8×	48 0.4×	90 1.2×	21 0.4×	9	332
Fiana Raiber Israel	10	241 0.7×	215 0.7×	95 0.8×	64 0.9×	7 0.1×	31	344
Debapriyo Majumdar Germany	7	155 0.4×	156 0.5×	60 0.5×	160 2.2×	15 0.3×	17	315

Countries citing papers authored by Anna Shtok

Since Specialization

Citations

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

Fields of papers citing papers by Anna Shtok

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Shtok

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

All Works

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17 of 17 papers shown

1.

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

2.

Shtok, Anna, et al.. (2018). Testing the Cluster Hypothesis with Focused and Graded Relevance Judgments. 1173–1176. 4 indexed citations

3.

Shtok, Anna, et al.. (2016). A Probabilistic Fusion Framework. 1463–1472. 10 indexed citations

4.

Shtok, Anna, Oren Kurland, & David Carmel. (2016). Query Performance Prediction Using Reference Lists. ACM Transactions on Information Systems. 34(4). 1–34. 30 indexed citations

5.

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

6.

Shtok, Anna, et al.. (2016). Utilizing Focused Relevance Feedback. 1061–1064. 3 indexed citations

7.

Shtok, Anna, et al.. (2016). Query Expansion Using Word Embeddings. 1929–1932. 89 indexed citations

8.

Carmel, David, Anna Shtok, & Oren Kurland. (2013). Position-based contextualization for passage retrieval. 1241–1244. 5 indexed citations

9.

Shtok, Anna, et al.. (2013). Query-Performance Prediction Using Minimal Relevance Feedback. 14–21. 7 indexed citations

10.

Shtok, Anna, et al.. (2013). Estimating query representativeness for query-performance prediction. 853–856. 5 indexed citations

11.

Shtok, Anna, Gideon Dror, Yoelle Maarek, & Idan Szpektor. (2012). Learning from the past. 759–768. 82 indexed citations

12.

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

13.

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

14.

Shtok, Anna, et al.. (2012). Predicting Query Performance by Query-Drift Estimation. ACM Transactions on Information Systems. 30(2). 1–35. 94 indexed citations

15.

Kurland, Oren, Fiana Raiber, & Anna Shtok. (2012). Query-performance prediction and cluster ranking. 2459–2462. 10 indexed citations

16.

Shtok, Anna, et al.. (2012). Predicting query performance for fusion-based retrieval. 813–822. 14 indexed citations

17.

Shtok, Anna, Oren Kurland, & David Carmel. (2010). Using statistical decision theory and relevance models for query-performance prediction. 259–266. 48 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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