TagClouds is a popular visualization for the collaborative tags. However it has some instinct problems such as linguistic issues, high semantic density and poor understanding of hierarchical structure and semantic relation between tags. In this paper we investigate the ways to support semantic understanding of collaborative tags and propose an improved visualization named TagClusters. Based on ...

Semantic relatedness is a very important factor for the coreference resolution task. To obtain this semantic information, corpusbased approaches commonly leverage patterns that can express a specific semantic relation. The patterns, however, are designed manually and thus are not necessarily the most effective ones in terms of accuracy and breadth. To deal with this problem, in this paper we pr...

This paper proposes a method for measuring semantic similarity between words as a new tool for text analysis. The similarity is measured on a semantic network constructed systematically from a subset of the English dictionary, LDOCE (Longman Dictionary of Contemporary English). Spreading activation on the network can directly compute the similarity between any two words in the Longman De ning V...

The measurement of semantic relatedness between two words is an important metric for many natural language processing applications. In this paper, we present a novel approach for measuring semantic relatedness that is based on a weighted semantic network. This approach explores the use of a lexicon, semantic relation types as weights, and word definitions as a basis to calculate semantic relate...

This study examines the relationship between two kinds of semantic spaces — i.e., spaces based on term frequency (tf) and word cooccurrence frequency (co) — and four semantic relations — i.e., synonymy, coordination, superordination, and collocation — by comparing, for each semantic relation, the performance of two semantic spaces in predicting word association. The simulation experiment demons...