Escaping the Trap of too Precise Topic Queries
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 fuzzy matches but this introduces
noise which may prevent the user of understanding the function of the
search engine.
In this paper, we propose a way to escape the topic trap by employing the
navigation between related topics and the count of search results for each
topic. This supports the user in that search for close-by topics is a
click away from a previous search. This approach was realized with the
i2geo search engine and is described in detail where the relation of being
{\it related} is computed by employing textual analysis of the definitions
of the concepts fetched from the Wikipedia encyclopedia.
Published:
Intelligent Computer Mathematics, Proceedings of CICM 2013, Bath UK,
Lecture Notes in Computer Science, Volume 7961,
Jacques Carette, David Aspinall, Christoph Lange, Petr Sojka, Wolfgang Windsteiger (Eds.),
ISBN: 978-3-642-39319-8
, 2013-07