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Pucktada Treeratpituk 的论文(13) 排序方式:
Graph-based Approach to Automatic Taxonomy Generation (GraBTax)  
Computing Research Repository  2013
0次引用 0 0
CSSeer: an expert recommendation system based on CiteseerX  
We propose CSSeer, a free and publicly available keyphrase based recommendation system for expert discovery based on the CiteSeerX digital library and Wikipedia as an auxiliary resource. CSSeer genera......
ACM/IEEE Joint Conference on Digital Libraries  2013
0次引用 0 0
AckSeer: a repository and search engine for automatically extracted acknowledgments from digital libraries  
Acknowledgments are widely used in scientific articles to express gratitude and credit collaborators. Despite suggestions that indexing acknowledgments automatically will give interesting insights, th......
ACM/IEEE Joint Conference on Digital Libraries  2012
2次引用 0 0
Name-Ethnicity Classification and Ethnicity-Sensitive Name Matching  
National Conference on Artificial Intelligence  2012
0次引用 0 0
Specialized Research Datasets in the CiteSeer x Digital Library  
D-lib Magazine  2012
0次引用 0 0
Entity resolution using search engine results  
International Conference on Information and Knowledge Management  2012
0次引用 0 0
Enhancing Cross Document Coreference of Web Documents with Context Similarity and Very Large Scale Text Categorization  
Cross Document Coreference (CDC) is the task of constructing the coreference chain for mentions of a person across a set of documents. This work offers a holistic view of using document-level categori......
International Conference on Computational Linguistics  2010
1次引用 0 0
Disambiguating authors in academic publications using random forests  
Users of digital libraries usually want to know the exact author or authors of an article. But different authors may share the same names, either as full names or as initials and last names (complete ......
ACM/IEEE Joint Conference on Digital Libraries  2009
19次引用 0 0
Automatically labeling hierarchical clusters  
Government agencies must often quickly organize and analyze large amounts of textual information, for example comments received as part of notice and comment rulemaking. Hierarchical organization is p......
DG.O National Conference on Digital Government Research  2006
29次引用 0 0
An experimental study on automatically labeling hierarchical clusters using statistical features  
Research and Development in Information Retrieval  2006
4次引用 0 0

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