Where you like to go next: successive point-of-interest recommendation

338 indexed citations

Abstract

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About

This paper, published in 2013, received 338 indexed citations. Written by Cheng Chen, Haiqin Yang, Michael R. Lyu and Irwin King covering the research area of Signal Processing, Transportation and Information Systems. It is primarily cited by scholars working on Information Systems (261 citations), Transportation (256 citations) and Signal Processing (79 citations). Published in International Joint Conference on Artificial Intelligence.

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Countries where authors are citing Where you like to go next: successive point-of-interest recommendation

Specialization
Citations

This map shows the geographic impact of Where you like to go next: successive point-of-interest recommendation. 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 Where you like to go next: successive point-of-interest recommendation with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Where you like to go next: successive point-of-interest recommendation more than expected).

Fields of papers citing Where you like to go next: successive point-of-interest recommendation

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Where you like to go next: successive point-of-interest recommendation. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Where you like to go next: successive point-of-interest recommendation.

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.

This paper is also available at doi.org/w17945999.

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