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» Detecting Co-Derivative Documents in Large Text Collections
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INTERSPEECH
2010
14 years 4 months ago
Constructing Japanese test collections for spoken term detection
Spoken Document Retrieval (SDR) and Spoken Term Detection (STD) have been two of the most intensively investigated topics in spoken document processing research according to the e...
Yoshiaki Itoh, Hiromitsu Nishizaki, Xinhui Hu, Hir...
WWW
2009
ACM
15 years 10 months ago
Detecting the origin of text segments efficiently
In the origin detection problem an algorithm is given a set S of documents, ordered by creation time, and a query document D. It needs to output for every consecutive sequence of ...
Ossama Abdel Hamid, Behshad Behzadi, Stefan Christ...
ICDM
2007
IEEE
147views Data Mining» more  ICDM 2007»
15 years 1 months ago
Improving Knowledge Discovery in Document Collections through Combining Text Retrieval and Link Analysis Techniques
In this paper, we present Concept Chain Queries (CCQ), a special case of text mining in document collections focusing on detecting links between two topics across text documents. ...
Wei Jin, Rohini K. Srihari, Hung Hay Ho, Xin Wu
AI
2007
Springer
15 years 3 months ago
Fuzzy Clustering for Topic Analysis and Summarization of Document Collections
Abstract. Large document collections, such as those delivered by Internet search engines, are difficult and time-consuming for users to read and analyse. The detection of common an...
René Witte, Sabine Bergler
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 10 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum