The Journal of Machine Learning Research
A probabilistic approach to spatiotemporal theme pattern mining on weblogs
Proceedings of the 15th international conference on World Wide Web
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Comparing and evaluating information retrieval algorithms for news recommendation
Proceedings of the 2007 ACM conference on Recommender systems
Personalized Location-Based Recommendation Services for Tour Planning in Mobile Tourism Applications
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Latent dirichlet allocation for tag recommendation
Proceedings of the third ACM conference on Recommender systems
Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
GeoFolk: latent spatial semantics in web 2.0 social media
Proceedings of the third ACM international conference on Web search and data mining
The importance of link evidence in Wikipedia
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Location recommendation for location-based social networks
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
A latent variable model for geographic lexical variation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A location based reminder system for advertisement
Proceedings of the international conference on Multimedia
Concept-Based Information Retrieval Using Explicit Semantic Analysis
ACM Transactions on Information Systems (TOIS)
Geographical topic discovery and comparison
Proceedings of the 20th international conference on World wide web
Expert Systems with Applications: An International Journal
CityVoyager: an outdoor recommendation system based on user location history
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
Discovering geographical topics in the twitter stream
Proceedings of the 21st international conference on World Wide Web
GeoFeed: A Location Aware News Feed System
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Location-based recommendation system using Bayesian user's preference model in mobile devices
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
Geo-location inference on news articles via multimodal pLSA
Proceedings of the 20th ACM international conference on Multimedia
Location Comparison through Geographical Topics
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Modeling and broadening temporal user interest in personalized news recommendation
Expert Systems with Applications: An International Journal
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The interest of users in handheld devices is strongly related to their location. Therefore, the user location is important, as a user context, for news article recommendation in a mobile environment. This paper proposes a novel news article recommendation that reflects the geographical context of the user. For this purpose, we propose the Explicit Localized Semantic Analysis (ELSA), an ESA-based topical representation of documents. Every location has its own geographical topics, which can be captured from the geo-tagged documents related to the location. Thus, not only news articles but locations are also represented as topic vectors. The main advantage of ELSA is that it stresses only the topics that are relevant to a given location, whereas all topics are equally important in ESA. As a result, geographical topics have different importance according to the user location in ELSA, even if they come from the same article. Another advantage of ELSA is that it allows a simple comparison of the user location and news articles, because it projects both locations and articles onto an identical space composed of Wikipedia topics. In the evaluation of ELSA with the New York Times corpus, it outperformed two simple baselines of Bag-Of-Words and LDA as well as two ESA-based methods. Rt10 of ELSA was improved up to 46.25% over other methods, and its NDCG@k was always higher than those of the others regardless of k.