Merging and ranking answers in the semantic web: the wisdom of crowds

Vanessa Lopez; Andriy Nikolov; Miriam Fernandez; Marta Sabou; Victoria Uren; Enrico Motta

doi:10.1007/978-3-642-10871-6_10

Merging and ranking answers in the semantic web: the wisdom of crowds

Vanessa Lopez
, Andriy Nikolov
, Miriam Fernandez
, Marta Sabou
, Victoria Uren
, Enrico Motta

Open University

Research output: Chapter in Book/Published conference output › Conference publication

15 Citations (Scopus)

Abstract

In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our proposal includes a merging algorithm that aggregates, combines and filters ontology-based search results and three different ranking algorithms that sort the final answers according to different criteria such as popularity, confidence and semantic interpretation of results. An experimental evaluation on a large scale corpus indicates improvements in the quality of the search results with respect to a scenario where the merging and ranking algorithms were not applied. These collective methods for merging and ranking allow to answer questions that are distributed across ontologies, while at the same time, they can filter irrelevant answers, fuse similar answers together, and elicit the most accurate answer(s) to a question.

Original language	English
Title of host publication	The semantic web
Subtitle of host publication	fourth Asian conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings
Editors	Asunción Gómez-Pérez, Yong Yu, Ying Ding
Place of Publication	Berlin (DE)
Publisher	Springer
Pages	135-152
Number of pages	18
Volume	5926 LNCS
ISBN (Electronic)	978-3-642-10871-6
ISBN (Print)	978-3-642-10870-9
DOIs	https://doi.org/10.1007/978-3-642-10871-6_10
Publication status	Published - 2009
Event	4th Annual Asian Semantic Web Conference - Shanghai, China Duration: 6 Dec 2009 → 9 Dec 2009

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Volume	5926
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th Annual Asian Semantic Web Conference
Abbreviated title	ASWC 2009
Country/Territory	China
City	Shanghai
Period	6/12/09 → 9/12/09

Keywords

question answering
ranking
merging
fusion
semantic web

Access to Document

10.1007/978-3-642-10871-6_10

Cite this

Lopez, V., Nikolov, A., Fernandez, M., Sabou, M., Uren, V., & Motta, E. (2009). Merging and ranking answers in the semantic web: the wisdom of crowds. In A. Gómez-Pérez, Y. Yu, & Y. Ding (Eds.), The semantic web: fourth Asian conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings (Vol. 5926 LNCS, pp. 135-152). (Lecture notes in computer science; Vol. 5926). Springer. https://doi.org/10.1007/978-3-642-10871-6_10

Lopez, Vanessa ; Nikolov, Andriy ; Fernandez, Miriam et al. / Merging and ranking answers in the semantic web : the wisdom of crowds. The semantic web: fourth Asian conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings. editor / Asunción Gómez-Pérez ; Yong Yu ; Ying Ding. Vol. 5926 LNCS Berlin (DE) : Springer, 2009. pp. 135-152 (Lecture notes in computer science).

@inproceedings{8e0afff11be941fcb5a381c56c06d468,

title = "Merging and ranking answers in the semantic web: the wisdom of crowds",

abstract = "In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our proposal includes a merging algorithm that aggregates, combines and filters ontology-based search results and three different ranking algorithms that sort the final answers according to different criteria such as popularity, confidence and semantic interpretation of results. An experimental evaluation on a large scale corpus indicates improvements in the quality of the search results with respect to a scenario where the merging and ranking algorithms were not applied. These collective methods for merging and ranking allow to answer questions that are distributed across ontologies, while at the same time, they can filter irrelevant answers, fuse similar answers together, and elicit the most accurate answer(s) to a question.",

keywords = "question answering, ranking, merging, fusion, semantic web",

author = "Vanessa Lopez and Andriy Nikolov and Miriam Fernandez and Marta Sabou and Victoria Uren and Enrico Motta",

year = "2009",

doi = "10.1007/978-3-642-10871-6\_10",

language = "English",

isbn = "978-3-642-10870-9",

volume = "5926 LNCS",

series = "Lecture notes in computer science",

publisher = "Springer",

pages = "135--152",

editor = "Asunci{\'o}n G{\'o}mez-P{\'e}rez and Yong Yu and Ying Ding",

booktitle = "The semantic web",

address = "Germany",

note = "4th Annual Asian Semantic Web Conference, ASWC 2009 ; Conference date: 06-12-2009 Through 09-12-2009",

}

Lopez, V, Nikolov, A, Fernandez, M, Sabou, M, Uren, V & Motta, E 2009, Merging and ranking answers in the semantic web: the wisdom of crowds. in A Gómez-Pérez, Y Yu & Y Ding (eds), The semantic web: fourth Asian conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings. vol. 5926 LNCS, Lecture notes in computer science, vol. 5926, Springer, Berlin (DE), pp. 135-152, 4th Annual Asian Semantic Web Conference, Shanghai, China, 6/12/09. https://doi.org/10.1007/978-3-642-10871-6_10

Merging and ranking answers in the semantic web: the wisdom of crowds. / Lopez, Vanessa; Nikolov, Andriy; Fernandez, Miriam et al.
The semantic web: fourth Asian conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings. ed. / Asunción Gómez-Pérez; Yong Yu; Ying Ding. Vol. 5926 LNCS Berlin (DE): Springer, 2009. p. 135-152 (Lecture notes in computer science; Vol. 5926).

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - Merging and ranking answers in the semantic web

T2 - 4th Annual Asian Semantic Web Conference

AU - Lopez, Vanessa

AU - Nikolov, Andriy

AU - Fernandez, Miriam

AU - Sabou, Marta

AU - Uren, Victoria

AU - Motta, Enrico

PY - 2009

Y1 - 2009

N2 - In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our proposal includes a merging algorithm that aggregates, combines and filters ontology-based search results and three different ranking algorithms that sort the final answers according to different criteria such as popularity, confidence and semantic interpretation of results. An experimental evaluation on a large scale corpus indicates improvements in the quality of the search results with respect to a scenario where the merging and ranking algorithms were not applied. These collective methods for merging and ranking allow to answer questions that are distributed across ontologies, while at the same time, they can filter irrelevant answers, fuse similar answers together, and elicit the most accurate answer(s) to a question.

AB - In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our proposal includes a merging algorithm that aggregates, combines and filters ontology-based search results and three different ranking algorithms that sort the final answers according to different criteria such as popularity, confidence and semantic interpretation of results. An experimental evaluation on a large scale corpus indicates improvements in the quality of the search results with respect to a scenario where the merging and ranking algorithms were not applied. These collective methods for merging and ranking allow to answer questions that are distributed across ontologies, while at the same time, they can filter irrelevant answers, fuse similar answers together, and elicit the most accurate answer(s) to a question.

KW - question answering

KW - ranking

KW - merging

KW - fusion

KW - semantic web

UR - https://www.scopus.com/pages/publications/77049107989

UR - http://link.springer.com/chapter/10.1007/978-3-642-10871-6_10

U2 - 10.1007/978-3-642-10871-6_10

DO - 10.1007/978-3-642-10871-6_10

M3 - Conference publication

SN - 978-3-642-10870-9

VL - 5926 LNCS

T3 - Lecture notes in computer science

SP - 135

EP - 152

BT - The semantic web

A2 - Gómez-Pérez, Asunción

A2 - Yu, Yong

A2 - Ding, Ying

PB - Springer

CY - Berlin (DE)

Y2 - 6 December 2009 through 9 December 2009

ER -

Lopez V, Nikolov A, Fernandez M, Sabou M, Uren V, Motta E. Merging and ranking answers in the semantic web: the wisdom of crowds. In Gómez-Pérez A, Yu Y, Ding Y, editors, The semantic web: fourth Asian conference, ASWC 2009, Shanghai, China, December 6-9, 2009. Proceedings. Vol. 5926 LNCS. Berlin (DE): Springer. 2009. p. 135-152. (Lecture notes in computer science). doi: 10.1007/978-3-642-10871-6_10

Merging and ranking answers in the semantic web: the wisdom of crowds

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution

Supervising Doctoral Students

Cite this

Merging and ranking answers in the semantic web: the wisdom of crowds

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Research output

Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution

Activities

Supervising Doctoral Students

Cite this