Spatial information retrieval and geographical ontologies an overview of the SPIRIT project
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Computing Geographical Scopes of Web Resources
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Named Entity recognition without gazetteers
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Web-a-where: geotagging web content
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A comparison of methods for the automatic identification of locations in wikipedia
Proceedings of the 4th ACM workshop on Geographical information retrieval
Spatial variation in search engine queries
Proceedings of the 17th international conference on World Wide Web
Extracting geographic features from the Internet to automatically build detailed regional gazetteers
International Journal of Geographical Information Science
A Model for Geographic Knowledge Extraction on Web Documents
ER '09 Proceedings of the ER 2009 Workshops (CoMoL, ETheCoM, FP-UML, MOST-ONISW, QoIS, RIGiM, SeCoGIS) on Advances in Conceptual Modeling - Challenging Perspectives
Hi-index | 0.00 |
Finding automatic ways of attaching geographical scopes to on-line resources, also called “geo-referencing” documents, is a challenging problem, getting increasing attention [1,5,3]. Here we present a system architecture and a process for identifying the geographical scope of Web pages, defining a scope as the region where more people than average would find that page relevant. We rely on typical Web IR heuristics (i.e. feature weighting, hypertext topic locality, anchor description) and assumptions on how people use geographical references in documents. The method involves three major steps. First, geographical named entities are identified in the text. Next, we propagate the found named entities through the Web linkage graph. Finally, a geographical ontology is used to disambiguate among the named entities associated to a document, this way selecting the most likely scope. In the future, we plan on using scopes in new location-aware search tools.