Multi-domain search answers to queries spanning multiple entities, like "Find a hotel in Milan close to a concert venue, a museum and a good restaurant", by producing ranked sets of entity combinations that maximize relevance, measured by a function expressing the user's preferences. Due to the combinatorial nature of results, good entity instances (e.g., five stars hotels) tend to appear repeatedly in top-ranked combinations. To improve the quality of the result set, it is important to balance relevance with diversity, which promotes different, yet almost equally relevant, entities in the top-k combinations. This paper explores two different notions of diversity for multi-domain result sets, compares experimentally alternative algorithms for the trade-off between relevance and diversity, and performs a user study for evaluating the utility of diversification in multi-domain queries.

Original languageEnglish
Title of host publicationWeb Engineering - 12th International Conference, ICWE 2012, Proceedings
Place of PublicationBerlin
Number of pages16
Volume7387 LNCS
ISBN (Print)9783642317521
Publication statusPublished - 2012
Externally publishedYes
EventICWE 2012: 12th International Conference on Web Engineering - Berlin, Germany
Duration: 23 Jul 201227 Jul 2012
Conference number: 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7387 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


ConferenceICWE 2012

    Research areas

  • Greedy Algorithm, User Study, Relevance Score, Total Price, Entity Instance

ID: 33899105