Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
The Journal of Machine Learning Research
Author name disambiguation for citations on the deep web
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
Combining machine learning and human judgment in author disambiguation
Proceedings of the 20th ACM international conference on Information and knowledge management
AUTOMATIC ANNOTATION OF AMBIGUOUS PERSONAL NAMES ON THE WEB
Computational Intelligence
| Hi-index | 0.00 |
Name ambiguity is a special case of identity uncertainty where one person can be referenced by multiple name variations in different situations or evenshare the same name with other people. In this paper, we present an efficient framework by using two novel topic-based models, extended from Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA). Our models explicitly introduce a new variable for persons and learn the distribution of topics with regard to persons and words. Experiments indicate that our approach consistently outperforms other unsupervised methods including spectral and DBSCAN clustering. Scalability is addressed by disambiguating authors in over 750,000 papers from the entire CiteSeer dataset.