Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
The Journal of Machine Learning Research
Location Based Services
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Detecting dominant locations from search queries
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Learning a spelling error model from search query logs
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Cross-lingual query suggestion using query logs of different languages
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Mining geographic knowledge using location aware topic model
Proceedings of the 4th ACM workshop on Geographical information retrieval
Analysis of geographic queries in a search engine log
Proceedings of the first international workshop on Location and the web
Introduction to Information Retrieval
Introduction to Information Retrieval
Discovering users' specific geo intention in web search
Proceedings of the 18th international conference on World wide web
Annotation of URLs: more than the sum of parts
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Analyzing and evaluating query reformulation strategies in web search logs
Proceedings of the 18th ACM conference on Information and knowledge management
GeoFolk: latent spatial semantics in web 2.0 social media
Proceedings of the third ACM international conference on Web search and data mining
Distributed Algorithms for Topic Models
The Journal of Machine Learning Research
Equip tourists with knowledge mined from travelogues
Proceedings of the 19th international conference on World wide web
A latent variable model for geographic lexical variation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Personalizing web search using long term browsing history
Proceedings of the fourth ACM international conference on Web search and data mining
Geographical topic discovery and comparison
Proceedings of the 20th international conference on World wide web
Context-aware search personalization with concept preference
Proceedings of the 20th ACM international conference on Information and knowledge management
Panorama: a semantic-aware application search framework
Proceedings of the 16th International Conference on Extending Database Technology
Mining web search topics with diverse spatiotemporal patterns
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Dynamic multi-faceted topic discovery in twitter
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Fast topic discovery from web search streams
Proceedings of the 23rd international conference on World wide web
Hi-index | 0.00 |
Search engine query log is an important information source that contains millions of users' interests and information needs. In this paper, we tackle the problem of discovering latent geographic search topics via mining search engine query logs. A novel framework G-WSTD that contains search session derivation, geographic information extraction and geographic search topic discovery is developed to support a variety of downstream web applications. The core components of the framework are two topic models, which discover geographic search topics from two different perspectives. The first one is the Discrete Search Topic Model (DSTM), which aims to capture the semantic commonalities across discrete geographic locations. The second one is the Regional Search Topic Model (RSTM), which focuses on a specific region on the map and discovers web search topics that demonstrate geographic locality. We evaluate our framework against several strong baselines on a real-life query log. The framework demonstrates improved data interpretability, better prediction performance and higher topic distinctiveness in the experimentation. The effectiveness of the framework is also verified by applications such as user profiling and URL annotation.