Standard

Perceptual relational attributes : Navigating and discovering shared perspectives from user-generated reviews. / Torre, Manuel Valle; Ye, Mengmeng; Lofi, Christoph.

Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019. ed. / Torsten Grust; Felix Naumann; Alexander Bohm; Wolfgang Lehner; Theo Harder; Erhard Rahm; Andreas Heuer; Meike Klettke; Holger Meyer. Vol. P-289 Gesellschaft fur Informatik (GI), 2019. p. 169-189.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Torre, MV, Ye, M & Lofi, C 2019, Perceptual relational attributes: Navigating and discovering shared perspectives from user-generated reviews. in T Grust, F Naumann, A Bohm, W Lehner, T Harder, E Rahm, A Heuer, M Klettke & H Meyer (eds), Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019. vol. P-289, Gesellschaft fur Informatik (GI), pp. 169-189, Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019 - Database Systems for Business, Technology and Web, BTW 2019 and 18th Symposium of the GI Department "Databases and Information Systems", DBIS 2019, Rostock, Germany, 4/03/19. https://doi.org/10.18420/btw2019-11

APA

Torre, M. V., Ye, M., & Lofi, C. (2019). Perceptual relational attributes: Navigating and discovering shared perspectives from user-generated reviews. In T. Grust, F. Naumann, A. Bohm, W. Lehner, T. Harder, E. Rahm, A. Heuer, M. Klettke, ... H. Meyer (Eds.), Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019 (Vol. P-289, pp. 169-189). Gesellschaft fur Informatik (GI). https://doi.org/10.18420/btw2019-11

Vancouver

Torre MV, Ye M, Lofi C. Perceptual relational attributes: Navigating and discovering shared perspectives from user-generated reviews. In Grust T, Naumann F, Bohm A, Lehner W, Harder T, Rahm E, Heuer A, Klettke M, Meyer H, editors, Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019. Vol. P-289. Gesellschaft fur Informatik (GI). 2019. p. 169-189 https://doi.org/10.18420/btw2019-11

Author

Torre, Manuel Valle ; Ye, Mengmeng ; Lofi, Christoph. / Perceptual relational attributes : Navigating and discovering shared perspectives from user-generated reviews. Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019. editor / Torsten Grust ; Felix Naumann ; Alexander Bohm ; Wolfgang Lehner ; Theo Harder ; Erhard Rahm ; Andreas Heuer ; Meike Klettke ; Holger Meyer. Vol. P-289 Gesellschaft fur Informatik (GI), 2019. pp. 169-189

BibTeX

@inproceedings{fed231a138dc4ba589bd717994022a51,
title = "Perceptual relational attributes: Navigating and discovering shared perspectives from user-generated reviews",
abstract = "Effectively modelling and querying experience items like movies, books, or games in databases is challenging because these items are better described by their resulting user experience or perceived properties than by factual attributes. However, such information is often subjective, disputed, or unclear. Thus, social judgments like comments, reviews, discussions, or ratings have become a ubiquitous component of most Web applications dealing with such items, especially in the e-commerce domain. However, they usually do not play major role in the query process, and are typically just shown to the user. In this paper, we will discuss how to use unstructured user reviews to build a structured semantic representation of database items such that these perceptual attributes are (at least implicitly) represented and usable for navigational queries. Especially, we argue that a central challenge when extracting perceptual attributes from social judgments is respecting the subjectivity of expressed opinions. We claim that no representation consisting of only a single tuple will be sufficient. Instead, such systems should aim at discovering shared perspectives, representing dominant perceptions and opinions, and exploiting those perspectives for query processing.",
keywords = "Modelling, Perceptual Attributes, Query-By-Example Navigation, User-Generated Attribute Values",
author = "Torre, {Manuel Valle} and Mengmeng Ye and Christoph Lofi",
year = "2019",
doi = "10.18420/btw2019-11",
language = "English",
volume = "P-289",
pages = "169--189",
editor = "Torsten Grust and Felix Naumann and Alexander Bohm and Wolfgang Lehner and Theo Harder and Erhard Rahm and Andreas Heuer and Meike Klettke and Holger Meyer",
booktitle = "Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs {"}Datenbanken und Informationssysteme{"}, DBIS 2019",
publisher = "Gesellschaft fur Informatik (GI)",
address = "Germany",

}

RIS

TY - GEN

T1 - Perceptual relational attributes

T2 - Navigating and discovering shared perspectives from user-generated reviews

AU - Torre, Manuel Valle

AU - Ye, Mengmeng

AU - Lofi, Christoph

PY - 2019

Y1 - 2019

N2 - Effectively modelling and querying experience items like movies, books, or games in databases is challenging because these items are better described by their resulting user experience or perceived properties than by factual attributes. However, such information is often subjective, disputed, or unclear. Thus, social judgments like comments, reviews, discussions, or ratings have become a ubiquitous component of most Web applications dealing with such items, especially in the e-commerce domain. However, they usually do not play major role in the query process, and are typically just shown to the user. In this paper, we will discuss how to use unstructured user reviews to build a structured semantic representation of database items such that these perceptual attributes are (at least implicitly) represented and usable for navigational queries. Especially, we argue that a central challenge when extracting perceptual attributes from social judgments is respecting the subjectivity of expressed opinions. We claim that no representation consisting of only a single tuple will be sufficient. Instead, such systems should aim at discovering shared perspectives, representing dominant perceptions and opinions, and exploiting those perspectives for query processing.

AB - Effectively modelling and querying experience items like movies, books, or games in databases is challenging because these items are better described by their resulting user experience or perceived properties than by factual attributes. However, such information is often subjective, disputed, or unclear. Thus, social judgments like comments, reviews, discussions, or ratings have become a ubiquitous component of most Web applications dealing with such items, especially in the e-commerce domain. However, they usually do not play major role in the query process, and are typically just shown to the user. In this paper, we will discuss how to use unstructured user reviews to build a structured semantic representation of database items such that these perceptual attributes are (at least implicitly) represented and usable for navigational queries. Especially, we argue that a central challenge when extracting perceptual attributes from social judgments is respecting the subjectivity of expressed opinions. We claim that no representation consisting of only a single tuple will be sufficient. Instead, such systems should aim at discovering shared perspectives, representing dominant perceptions and opinions, and exploiting those perspectives for query processing.

KW - Modelling

KW - Perceptual Attributes

KW - Query-By-Example Navigation

KW - User-Generated Attribute Values

UR - http://www.scopus.com/inward/record.url?scp=85072106773&partnerID=8YFLogxK

U2 - 10.18420/btw2019-11

DO - 10.18420/btw2019-11

M3 - Conference contribution

VL - P-289

SP - 169

EP - 189

BT - Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019

A2 - Grust, Torsten

A2 - Naumann, Felix

A2 - Bohm, Alexander

A2 - Lehner, Wolfgang

A2 - Harder, Theo

A2 - Rahm, Erhard

A2 - Heuer, Andreas

A2 - Klettke, Meike

A2 - Meyer, Holger

PB - Gesellschaft fur Informatik (GI)

ER -

ID: 66629524