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Computer Science > Information Retrieval

arXiv:1804.11131 (cs)
[Submitted on 30 Apr 2018]

Title:Author-topic profiles for academic search

Authors:Suzan Verberne, Arjen P. de Vries, Wessel Kraaij
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Abstract:We implemented and evaluated a two-stage retrieval method for personalized academic search in which the initial search results are re-ranked using an author-topic profile. In academic search tasks, the user's own data can help optimizing the ranking of search results to match the searcher's specific individual needs. The author-topic profile consists of topic-specific terms, stored in a graph. We re-rank the top-1000 retrieved documents using ten features that represent the similarity between the document and the author-topic graph. We found that the re-ranking gives a small but significant improvement over the reproduced best method from the literature. Storing the profile as a graph has a number of advantages: it is flexible with respect to node and relation types; it is a visualization of knowledge that is interpretable by the user, and it offers the possibility to view relational characteristics of individual nodes.
Comments: 13 pages, 1 figure
Subjects: Information Retrieval (cs.IR)
Cite as: arXiv:1804.11131 [cs.IR]
  (or arXiv:1804.11131v1 [cs.IR] for this version)
  https://doi.org/10.48550/arXiv.1804.11131

Submission history

From: Suzan Verberne [view email]
[v1] Mon, 30 Apr 2018 11:43:12 UTC (1,372 KB)
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