Diversification for multi-domain result sets

Alessandro Bozzon; Marco Brambilla; Piero Fraternali; Marco Tagliasacchi

doi:10.1007/978-3-642-31753-8_10

Diversification for multi-domain result sets

Alessandro Bozzon^*, Marco Brambilla, Piero Fraternali, Marco Tagliasacchi

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	Web Engineering - 12th International Conference, ICWE 2012, Proceedings
Place of Publication	Berlin
Publisher	Springer
Pages	137-152
Number of pages	16
Volume	7387 LNCS
ISBN (Print)	9783642317521
DOIs	https://doi.org/10.1007/978-3-642-31753-8_10
Publication status	Published - 2012
Externally published	Yes
Event	ICWE 2012: 12th International Conference on Web Engineering - Berlin, Germany Duration: 23 Jul 2012 → 27 Jul 2012 Conference number: 12

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7387 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	ICWE 2012
Country/Territory	Germany
City	Berlin
Period	23/07/12 → 27/07/12

Keywords

Greedy Algorithm
User Study
Relevance Score
Total Price
Entity Instance

Access to Document

10.1007/978-3-642-31753-8_10

Cite this

Bozzon, A., Brambilla, M., Fraternali, P., & Tagliasacchi, M. (2012). Diversification for multi-domain result sets. In Web Engineering - 12th International Conference, ICWE 2012, Proceedings (Vol. 7387 LNCS, pp. 137-152). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7387 LNCS). Springer. https://doi.org/10.1007/978-3-642-31753-8_10

Bozzon, Alessandro ; Brambilla, Marco ; Fraternali, Piero et al. / Diversification for multi-domain result sets. Web Engineering - 12th International Conference, ICWE 2012, Proceedings. Vol. 7387 LNCS Berlin : Springer, 2012. pp. 137-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Diversification for multi-domain result sets",

abstract = "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.",

keywords = "Greedy Algorithm, User Study, Relevance Score, Total Price, Entity Instance",

author = "Alessandro Bozzon and Marco Brambilla and Piero Fraternali and Marco Tagliasacchi",

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doi = "10.1007/978-3-642-31753-8_10",

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Bozzon, A, Brambilla, M, Fraternali, P & Tagliasacchi, M 2012, Diversification for multi-domain result sets. in Web Engineering - 12th International Conference, ICWE 2012, Proceedings. vol. 7387 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7387 LNCS, Springer, Berlin, pp. 137-152, ICWE 2012, Berlin, Germany, 23/07/12. https://doi.org/10.1007/978-3-642-31753-8_10

Diversification for multi-domain result sets. / Bozzon, Alessandro; Brambilla, Marco; Fraternali, Piero et al.
Web Engineering - 12th International Conference, ICWE 2012, Proceedings. Vol. 7387 LNCS Berlin: Springer, 2012. p. 137-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7387 LNCS).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Brambilla, Marco

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AU - Tagliasacchi, Marco

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AB - 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.

KW - Greedy Algorithm

KW - User Study

KW - Relevance Score

KW - Total Price

KW - Entity Instance

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Bozzon A, Brambilla M, Fraternali P, Tagliasacchi M. Diversification for multi-domain result sets. In Web Engineering - 12th International Conference, ICWE 2012, Proceedings. Vol. 7387 LNCS. Berlin: Springer. 2012. p. 137-152. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-31753-8_10

Diversification for multi-domain result sets

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Keywords

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