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Explanatory semantic relatedness and explicit spatialization for exploratory search
Abstract Exploratory search, in which a user investExploratory search, in which a user investigates complex concepts, is cumbersome with today's search engines. We present a new exploratory search approach that generates interactive visualizations of query concepts using thematic cartography (e.g. choropleth maps, heat maps). We show how the approach can be applied broadly across both geographic and non-geographic contexts through explicit spatialization, a novel method that leverages any figure or diagram - from a periodic table, to a parliamentary seating chart, to a world map - as a spatial search environment. We enable this capability by introducing explanatory semantic relatedness measures. These measures extend frequently-used semantic relatedness measures to not only estimate the degree of relatedness between two concepts, but also generate human-readable explanations for their estimates by mining Wikipedia's text, hyperlinks, and category structure. We implement our approach in a system called Atlasify, evaluate its key components, and present several use cases.components, and present several use cases.
Abstractsub Exploratory search, in which a user investExploratory search, in which a user investigates complex concepts, is cumbersome with today's search engines. We present a new exploratory search approach that generates interactive visualizations of query concepts using thematic cartography (e.g. choropleth maps, heat maps). We show how the approach can be applied broadly across both geographic and non-geographic contexts through explicit spatialization, a novel method that leverages any figure or diagram - from a periodic table, to a parliamentary seating chart, to a world map - as a spatial search environment. We enable this capability by introducing explanatory semantic relatedness measures. These measures extend frequently-used semantic relatedness measures to not only estimate the degree of relatedness between two concepts, but also generate human-readable explanations for their estimates by mining Wikipedia's text, hyperlinks, and category structure. We implement our approach in a system called Atlasify, evaluate its key components, and present several use cases.components, and present several use cases.
Bibtextype inproceedings  +
Doi 10.1145/2348283.2348341  +
Has author Brent Hecht + , Carton S.H. + , Mahmood Quaderi + , Johannes Schoning + , Raubal M. + , Darren Gergle + , Doug Downey +
Has extra keyword Exploratory search + , Geography + , Giscience + , Semantic relatedness + , Spatialization + , Text mining + , Wikipedia + , Data mining + , Hypertext systems + , Information retrieval + , Mapping + , Map + , Search engine + , Websites + , Natural language processing systems +
Has keyword Cartography + , Exploratory search + , Geography + , Giscience + , Semantic relatedness + , Spatialization + , Text mining + , Wikipedia +
Isbn 9781450316583  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 415–424  +
Published in SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval +
Title Explanatory semantic relatedness and explicit spatialization for exploratory search +
Type conference paper  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 7 November 2014 18:27:20  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 18:27:20  +
DateThis property is a special property in this wiki. 2012  +
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