LODBookRec: Linked Open Data for Books Recommendation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10396527" target="_blank" >RIV/00216208:11320/19:10396527 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1145/3326467.3326476" target="_blank" >https://doi.org/10.1145/3326467.3326476</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3326467.3326476" target="_blank" >10.1145/3326467.3326476</a>

Result language

angličtina

Original language name

LODBookRec: Linked Open Data for Books Recommendation

Original language description

In this paper, we present the LODBookRec application. LODBookRec builds on top of Linked Open Data (LOD) knowledge about literature domain and provides information retrieval GUI to conveniently present this knowledge to the end users. As such, LODBookRec aims to contribute towards better utilization of LOD and provide a suitable platform for on-line evaluation of information retrieval methods, especially recommender systems. LODBookRec contains a basic search GUI and several recommendation methods, with the primary focus on item-based recommendations. The results of offline evaluation indicates that content-based recommendations utilizing attribute-based similarity of books provides best item-based recommendations w.r.t. recommendation relevance for both highly popular books as well as long-tail books. However, modification of the original algorithm via maximal margin relevance increases diversity of the recommended lists with a modest relevance penalties.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GJ19-22071Y" target="_blank" >GJ19-22071Y: Flexible models for known-item search in large video collections</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics

ISBN

978-1-4503-6190-3

ISSN

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e-ISSN

—

Number of pages

6

Pages from-to

1-6

Publisher name

ACM

Place of publication

New York, NY, USA

Event location

Seoul, Korea

Event date

Jun 26, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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