Details
| Original language | English |
|---|---|
| Title of host publication | WWW '21 |
| Subtitle of host publication | Companion Proceedings of the Web Conference 2021 |
| Place of Publication | New York |
| Pages | 685-686 |
| Number of pages | 2 |
| ISBN (electronic) | 9781450383134 |
| Publication status | Published - 19 Apr 2021 |
| Event | World Wide Web Conference (WWW 2021) - Ljubljana, Slovenia Duration: 19 Apr 2021 → 23 Apr 2021 Conference number: 30 |
Abstract
Scientists always look for the most accurate and relevant answer to their queries on the scholarly literature. Traditional scholarly search systems list documents instead of providing direct answers to the search queries. As data in knowledge graphs are not acquainted semantically, they are not machine-readable. Therefore, a search on scholarly knowledge graphs ends up in a full-Text search, not a search in the content of scholarly literature. In this demo, we present a faceted search system that retrieves data from a scholarly knowledge graph, which can be compared and filtered to better satisfy user information needs. Our practice's novelty is that we use dynamic facets, which means facets are not fixed and will change according to the content of a comparison.
Keywords
- Faceted Search, Information Retrieval, Knowledge Graph, Scholarly Knowledge, Search System
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Software
Cite this
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WWW '21: Companion Proceedings of the Web Conference 2021. New York, 2021. p. 685-686.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Demonstration of Faceted Search on Scholarly Knowledge Graphs
AU - Heidari, Golsa
AU - Ramadan, Ahmad
AU - Stocker, Markus
AU - Auer, Sören
N1 - Conference code: 30
PY - 2021/4/19
Y1 - 2021/4/19
N2 - Scientists always look for the most accurate and relevant answer to their queries on the scholarly literature. Traditional scholarly search systems list documents instead of providing direct answers to the search queries. As data in knowledge graphs are not acquainted semantically, they are not machine-readable. Therefore, a search on scholarly knowledge graphs ends up in a full-Text search, not a search in the content of scholarly literature. In this demo, we present a faceted search system that retrieves data from a scholarly knowledge graph, which can be compared and filtered to better satisfy user information needs. Our practice's novelty is that we use dynamic facets, which means facets are not fixed and will change according to the content of a comparison.
AB - Scientists always look for the most accurate and relevant answer to their queries on the scholarly literature. Traditional scholarly search systems list documents instead of providing direct answers to the search queries. As data in knowledge graphs are not acquainted semantically, they are not machine-readable. Therefore, a search on scholarly knowledge graphs ends up in a full-Text search, not a search in the content of scholarly literature. In this demo, we present a faceted search system that retrieves data from a scholarly knowledge graph, which can be compared and filtered to better satisfy user information needs. Our practice's novelty is that we use dynamic facets, which means facets are not fixed and will change according to the content of a comparison.
KW - Faceted Search
KW - Information Retrieval
KW - Knowledge Graph
KW - Scholarly Knowledge
KW - Search System
UR - http://www.scopus.com/inward/record.url?scp=85107647912&partnerID=8YFLogxK
U2 - 10.1145/3442442.3458605
DO - 10.1145/3442442.3458605
M3 - Conference contribution
AN - SCOPUS:85107647912
SP - 685
EP - 686
BT - WWW '21
CY - New York
T2 - World Wide Web Conference (WWW 2021)
Y2 - 19 April 2021 through 23 April 2021
ER -