This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and ...
Hakan Ceylan, Rada Mihalcea, Umut O'zertem, Elena ...
We propose that, at the highest level of video understanding, the human needs for meaning and the methodologies to extract it are both universal and generic. One must develop an o...
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...
We use clustering to derive new relations which augment database schema used in automatic generation of predictive features in statistical relational learning. Clustering improves...
Identifying the occurrences of proper names in text and the entities they refer to can be a difficult task because of the manyto-many mapping between names and their referents. We...