Escaping the Trap of too Precise Topic Queries
Paul Libbrecht

TL;DR
The paper addresses the problem of overly precise topic queries in digital mathematics libraries, proposing a navigation-based approach using related topics and search result counts to improve search effectiveness.
Contribution
It introduces a novel method employing related topics and search result counts, derived from Wikipedia definitions, to help users escape the topic trap in mathematical information retrieval.
Findings
Implemented in the i2geo search engine
Supports navigation between related topics
Reduces noise in fuzzy search results
Abstract
At the very center of digital mathematics libraries lie controlled vocabularies which qualify the {\it topic} of the documents. These topics are used when submitting a document to a digital mathematics library and to perform searches in a library. The latter are refined by the use of these topics as they allow a precise classification of the mathematics area this document addresses. However, there is a major risk that users employ too precise topics to specify their queries: they may be employing a topic that is only "close-by" but missing to match the right resource. We call this the {\it topic trap}. Indeed, since 2009, this issue has appeared frequently on the i2geo.net platform. Other mathematics portals experience the same phenomenon. An approach to solve this issue is to introduce tolerance in the way queries are understood by the user. In particular, the approach of including…
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Taxonomy
TopicsAdvanced Text Analysis Techniques · Mathematics, Computing, and Information Processing · Natural Language Processing Techniques
