This paper discusses linguistically motivated features for enhanced back-of-the-book indexing.

This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise.

This paper describes the English-Hindi Multilingual lexical sample task in SENSEVAL-3.

This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a text using the sense from WordNet. SenseLearner participated in the SENSEVAL-3 English all words task, and achieved an average accuracy of 64.6%.

This paper discusses measuring the semantic similarity of texts.

This paper discusses integrating knowledge for subjectivity sense labeling.

This article discusses semantic document engineering with WordNet and PageRank.

This paper discusses an evaluation exercise for word alignment.

This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks.

This paper discusses building a sense tagged corpus with Open Mind Word Expert, an implemented active learning system for collecting word sense tagging from the general public over the Web.

Article discussing networks and natural language processing. The authors present some of the most successful graph-based representations and algorithms used in language processing and try to explain how and why they work.

Article on canopy gaps and understory light spectrum in a Venezuelan Andean cloud forest.

This paper discusses automatic recognition of humor.

This article reviews the book "'The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data," by Ronen Feldman and James Sanger.

This paper discusses learning to identify educational materials.

This paper discusses word sense and subjectivity.

This paper discusses automatic generating of back-of-the-book indexes.

This paper investigates the problem of automatic humor recognition, and provides an in-depth analysis of two of the most frequently observed features of humorous text: human-centeredness and negative polarity. Through experiments performed on two collections of humorous texts, the authors show that these properties of verbal humor are consisted across different data sets.

In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications.

This paper discusses global versus local call admission control.

This paper discusses multilingual subjectivity analysis using machine translation.

This paper investigates the application of co-training and self-training to word sense disambiguation. Optimal and empirical parameter selection methods for co-training and self-training are investigated, with various degrees of error reduction. A new method that combines co-training with majority voting is introduced, with the effect of smoothing the bootstrapping learning curves, and improving the average performance.

In this paper, the authors evaluate the extent to which human-written book summaries can be obtained through cut-and-paste operations from the original book. The authors analyze the effect of the parameters involved in the decomposition algorithm, and highlight the distinctions in coverage obtained for different summary types.

This paper discusses linguistic ethnography.