Metric details for natural-language spatial relations
ACM Transactions on Information Systems (TOIS)
Learning dictionaries for information extraction by multi-level bootstrapping
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Discovering word senses from text
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Automatic construction of a hypernym-labeled noun hierarchy from text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A graph model for unsupervised lexical acquisition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Improvements in automatic thesaurus extraction
ULA '02 Proceedings of the ACL-02 workshop on Unsupervised lexical acquisition - Volume 9
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Scaling distributional similarity to large corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Towards terascale knowledge acquisition
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Discovering geographic locations in web pages using urban addresses
Proceedings of the 4th ACM workshop on Geographical information retrieval
Geographic co-occurrence as a tool for gir.
Proceedings of the 4th ACM workshop on Geographical information retrieval
International Journal of Geographical Information Science
Mining Topological Relations from the Web
DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
GikiP: evaluating geographical answers from wikipedia
Proceedings of the 2nd international workshop on Geographic information retrieval
Feature generation for text categorization using world knowledge
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Geospatial route extraction from texts
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics
Class label enhancement via related instances
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Measuring the use of factual information in test-taker essays
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
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One of the most desired information types when planning a trip to some place is the knowledge of transport, roads and geographical connectedness of prominent sites in this place. While some transport companies or repositories make some of this information accessible, it is not easy to find, and the majority of information about uncommon places can only be found in web free text such as blogs and forums. In this paper we present an algorithmic framework which allows an automated acquisition of map-like information from the web, based on surface patterns like "from X to Y". Given a set of locations as initial seeds, we retrieve from the web an extended set of locations and produce a map-like network which connects these locations using transport type edges. We evaluate our framework in several settings, producing meaningful and precise connection sets.