Open Data for Local Search
| Autor: | Nizar Ghoula, Marie-Jean Meurs, Eric Charton |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Semantic search 02 engineering and technology Data science World Wide Web Search engine Open data 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Local search (optimization) business Semantic Web |
| Zdroj: | WWW (Companion Volume) |
| DOI: | 10.1145/2872518.2890487 |
| Popis: | Local search engines are specialized information retrieval systems enabling users to discover amenities and services in their neighbourhood. Developing a local search system still raises scientific questions, as well as very specific technical issues. Those issues come for example from the lack of information about local events and actors, or the specific form taken by the indexable data. Available open data can be exploited to dramatically improve the design of local search engines and their content. The purpose of this workshop is to explore new fields of investigation both in terms of algorithmic approaches as well as originality of usable data. The workshop focuses on how open data can be used to enhance the capabilities of local search engines. |
| Databáze: | OpenAIRE |
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