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SAC
2011
ACM
14 years 7 months ago
Towards discovering criminal communities from textual data
In many criminal cases, forensically collected data contain valuable information about a suspect’s social networks. An investigator often has to manually extract information fro...
Rabeah Al-Zaidy, Benjamin C. M. Fung, Amr M. Youss...
ICDM
2007
IEEE
133views Data Mining» more  ICDM 2007»
15 years 11 months ago
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Xuerui Wang, Andrew McCallum, Xing Wei
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
15 years 3 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
SIGIR
2009
ACM
15 years 11 months ago
A relevance-based topic model for news event tracking
Event tracking is the task of discovering temporal patterns of popular events from text streams. Existing approaches for event tracking have two limitations: scalability and inabi...
Viet Ha-Thuc, Yelena Mejova, Christopher Harris, P...
KCAP
2005
ACM
15 years 10 months ago
Extracting significant words from corpora for ontology extraction
This paper reports a technique for Knowledge Extraction using Natural Language Processing for the purposes of semi-automatic Ontology learning. Determination of significant words ...
Dileep G. Damle, Victoria S. Uren