Open Data for Local Search: Challenges and Perspectives

@article{Charton2016OpenDF,
  title={Open Data for Local Search: Challenges and Perspectives},
  author={Eric Charton and Nizar Ghoula and Marie-Jean Meurs},
  journal={Proceedings of the 25th International Conference Companion on World Wide Web},
  year={2016}
}
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… 
Querying Brazilian Educational Open Data using a Hybrid NLP-based Approach
TLDR
This paper proposes a hybrid NLP-based approach for querying Open Data of Brazilian Educational Census based on a combination of linguistic and rule-based NLP approaches, that are applied in two main processing stages to identify the meaning of an input question and optimize the querying process.

References

SHOWING 1-10 OF 17 REFERENCES
Semantic Enrichment for Local Search Engine using Linked Open Data
TLDR
The approach consists of semantically enriching the results of a query using Linked Open Data (LOD) web content, which will improve the effectiveness of local search, and increase the ranking of local businesses.
Open Data Business Licence Usage to Improve Local Search Engine Content Ranking
This paper addresses the use of Open Data business licence records in the course of local web search. It assesses the feasibility of increasing the search ranking of authorised service providers and
Improving Local Search with Open Geographic Data
TLDR
A model to infer user preferences that integrates geographic parameters is proposed and a new framework for ``local'' (in the sense of geography) search that offsets the absence of contexts regarding physical business units is developed.
Design and Implementation of a Geographic Search Engine
TLDR
The design and initial implementation of a geographic search engine prototype for Germany, based on a large crawl of the domain, is described, which performs massive extraction of geographic features from crawled data, which are then mapped to coordinates and aggregated across link and site structure.
Extracting Patterns and Relations from the World Wide Web
TLDR
This paper presents a technique which exploits the duality between sets of patterns and relations to grow the target relation starting from a small sample and uses it to extract a relation of (author,title) pairs from the World Wide Web.
Ontology Based Information Retrieval in Semantic Web: A Survey
TLDR
Semantic Web (SW) is a well defined portal that helps in extracting relevant information using many Information Retrieval (IR) techniques, and use of Ontology also contributes in building new generation of web- Semantic Web.
Weighted multi-attribute matching of user-generated points of interest
TLDR
This work presents a weighted multi-attribute matching strategy based on multiple attributes of Points of Interests from the Location-based Social Network Foursquare and the Yelp local directory service, and presents its performance.
An ontology-based retrieval system using semantic indexing
Linked Data - The Story So Far
TLDR
The authors describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked data community as it moves forward.
A Simple Tags Categorization Framework Using Spatial Coverage to Discover Geospatial Semantics
TLDR
This work proposes a logical approach to highlight and possibly discover the characteristics of geographic places, based on the notion of spatial coverage and a model of tags categorization and on their semantic identification, using semantic services such as GeoNames, OpenStreetMap or WordNet.
...
...