Kazuaki Kishida

21 papers receiving 231 citations

Peers

Kazuaki Kishida
Comparison fields: 5 of 54
  • Artificial Intelligence 216
  • Information Systems 127
  • Computer Vision and Pattern Recognition 40
  • Molecular Biology 23
  • Signal Processing 18
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Countries citing papers authored by Kazuaki Kishida

Since Specialization
Citations

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

Fields of papers citing papers by Kazuaki Kishida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kazuaki Kishida

This figure shows the co-authorship network connecting the top 25 collaborators of Kazuaki Kishida. A scholar is included among the top collaborators of Kazuaki Kishida 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 Kazuaki Kishida. Kazuaki Kishida 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
An Experiment on Simple and Practical Methods of Cluster Labeling for Hierarchically Organized Document Subsets
1
2
Empirical Comparison of External Evaluation Measures for Document Clustering by Using Synthetic Data
2
3 0
4 3
5
Vocabulary-based Re-ranking for Geographic and Temporal Searching at NTCIR GeoTime Task.
5
6 6
7 9
8 5
9
Property of average precision and its generalization: An examination of evaluation indicator for information retrieval experiments
68
10
Prediction of Performance on Cross-Lingual Information Retrieval by Regression Models.
2
11 2
12 47
13 2
14
Techniques of document clustering: A review
8
15
Two Stages Refinement of Query Translation for Pivot Language Approach to Cross Lingual Information Retrieval: A Trial at CLEF 2003
1
16 4
17
Experiment on Pseudo Relevance Feedback Method Using Taylor Formula at NTCIR-3 Patent Retrieval Task
12
18
Regression Model and Query Expansion for NTCIR-2 Ad Hoc Retrieval Task.
1
19
Comparing Multiple Methods for Japanese and Japanese-English Text Retrieval.
13
20 1

About Kazuaki Kishida

Kazuaki Kishida is a scholar working on Information Systems, Library and Information Sciences and Artificial Intelligence, having authored 23 papers that have together received 272 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (13 papers), Topic Modeling (6 papers) and Web Data Mining and Analysis (5 papers). The work is most often cited by research in Artificial Intelligence (216 citations), Information Systems (127 citations) and Computer Vision and Pattern Recognition (40 citations). Kazuaki Kishida has collaborated with scholars based in Japan, South Korea and Taiwan. Frequent co-authors include Noriko Kando, Koji Eguchi, Sukhoon Lee, Kuang‐Hua Chen, Sung Hyon Myaeng, Hsin‐Hsi Chen, Aitao Chen, Fredric C. Gey, Yoshiko Sato and Mark Sanderson. Their work appears in journals such as Information Processing & Management, Journal of Information Science and Library & Information Science Research.

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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