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CIKM
2010
Springer
13 years 9 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
ICPR
2004
IEEE
14 years 11 months ago
Incorporating Temporal Context with Content for Classifying Image Collections
Semantic scene classification is an open problem in image understanding, especially when information purely from image content (i.e., pixels) is employed. However, in applications...
Jiebo Luo, Matthew R. Boutell
ICDE
2007
IEEE
121views Database» more  ICDE 2007»
14 years 2 months ago
Evaluating Different Ranking Functions for Context-Based Literature Search
Context-based literature digital library search is a new search paradigm that creates an effective ranking of query outputs by controlling query output topic diversity. We define ...
Nattakarn Ratprasartporn, Sulieman Bani-Ahmad, Ali...
LREC
2008
93views Education» more  LREC 2008»
13 years 11 months ago
Using a Probabilistic Model of Context to Detect Word Obfuscation
This paper proposes a distributional model of word use and word meaning which is derived purely from a body of text, and then applies this model to determine whether certain words...
Sanaz Jabbari, Ben Allison, Louise Guthrie
CAISE
2004
Springer
14 years 3 months ago
A knowledge-based approach to ontology learning and semantic annotation
The so-called Semantic Web vision will certainly benefit from automatic semantic annotation of words in documents. We present a method, called structural semantic interconnections ...
Roberto Navigli, Paola Velardi