Combining interaction and content for feedback-based ranking

Emanuele Di Buccio; Massimo Melucci; Dawei Song

doi:10.1007/978-3-642-21353-3_5

Combining interaction and content for feedback-based ranking

Emanuele Di Buccio^*, Massimo Melucci, Dawei Song

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.

Original language	English
Title of host publication	Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings
Pages	46-61
Number of pages	16
DOIs	https://doi.org/10.1007/978-3-642-21353-3_5
Publication status	Published - 2011
Externally published	Yes
Event	2nd Information Retrieval Facility Conference, IRFC 2011 - Vienna, Austria Duration: 6 Jun 2011 → 6 Jun 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6653 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd Information Retrieval Facility Conference, IRFC 2011
Country/Territory	Austria
City	Vienna
Period	6/06/11 → 6/06/11

Access to Document

10.1007/978-3-642-21353-3_5

Cite this

Di Buccio, E., Melucci, M., & Song, D. (2011). Combining interaction and content for feedback-based ranking. In Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings (pp. 46-61). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6653 LNCS). https://doi.org/10.1007/978-3-642-21353-3_5

Di Buccio, Emanuele ; Melucci, Massimo ; Song, Dawei. / Combining interaction and content for feedback-based ranking. Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings. 2011. pp. 46-61 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{e73a1da4f48f43cfa5c4e3887d9d4942,

title = "Combining interaction and content for feedback-based ranking",

abstract = "The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.",

author = "{Di Buccio}, Emanuele and Massimo Melucci and Dawei Song",

year = "2011",

doi = "10.1007/978-3-642-21353-3_5",

language = "English",

isbn = "9783642213526",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "46--61",

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note = "2nd Information Retrieval Facility Conference, IRFC 2011 ; Conference date: 06-06-2011 Through 06-06-2011",

}

Di Buccio, E, Melucci, M & Song, D 2011, Combining interaction and content for feedback-based ranking. in Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6653 LNCS, pp. 46-61, 2nd Information Retrieval Facility Conference, IRFC 2011, Vienna, Austria, 6/06/11. https://doi.org/10.1007/978-3-642-21353-3_5

Combining interaction and content for feedback-based ranking. / Di Buccio, Emanuele; Melucci, Massimo; Song, Dawei.
Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings. 2011. p. 46-61 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6653 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Combining interaction and content for feedback-based ranking

AU - Di Buccio, Emanuele

AU - Melucci, Massimo

AU - Song, Dawei

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N2 - The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.

AB - The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.

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DO - 10.1007/978-3-642-21353-3_5

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings

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Di Buccio E, Melucci M, Song D. Combining interaction and content for feedback-based ranking. In Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings. 2011. p. 46-61. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-21353-3_5

Combining interaction and content for feedback-based ranking

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