Search engine such as Google and yahoo returns a list of web pages that match the user query. It is very difficult for the user to find relevant web pages. Cluster based search engine can provide significantly more powerful models for searching a user query. Clustering is a process of forming groups (clusters) of similar objects from a given set of inputs. When applied to web search results, cl...

This paper support the concept of a community Web directory, as a Web directory that is constructed according to the needs and interests of particular user communities. Furthermore, it presents the complete method for the construction of such directories by using web usage data. User community models take the form of thematic hierarchies and are constructed by employing clustering approach. We ...

The thematic and citation structures of Data and Knowledge Engineering (DKE) (1985–2007) are identified based on text analysis and citation analysis of the bibliographic records of full papers published in the journal. Temporal patterns are identified by detecting abrupt increases of frequencies of noun phrases extracted from titles and abstracts of DKE papers over time. Conceptual structures o...

Clustering textual contents is an important step in mining useful information on the web or other text-based resources. The common task in text clustering is to handle text in a multi-dimensional space, and to partition documents into groups, where each group contains documents that are similar to each other. However, this strategy lacks a comprehensive view for humans in general since it canno...

This article overviews research on second language vocabulary instruction with a specific focus on semantic and thematic vocabulary-clustering types. The theoretical benefits associated with both the semantic and thematic approaches, as well as the potential problems associated with them, are discussed. The conclusion drawn is that reinforcing the level of activation of target concepts during l...

We have developed a method for autonomous construction of thematic maps of Martian terrain from digital topography. These maps show spatial distribution of topographical features and are generated by a computer algorithm that classifies pixels on the basis of topographical information they carry. We apply our technique to generate a thematic map of Tisia Valles region on Mars. Introduction. The...

In this paper we introduce a machine learning approach for automatic text segmentation. Our text segmenter clusters text-segments containing similar concepts. It first discovers the different concepts present in a text, each concept being defined as a set of representative terms. After that the text is partitioned into coherent paragraphs using a clustering technique based on the Classification...

The thematic text segmentation task consists in identifying the most important thematic breaks in a document in order to cut it into homogeneous passages. We propose in this paper an algorithm for linear text segmentation on general corpuses. It relies on an initial clustering of the sentences of the text. This preliminary partitioning provides a global view on the sentences relations existing ...

Article history: Received 22 August 2014 Received in revised form 29 February 2016 Accepted 10 March 2016 Available online 8 April 2016 The use of satellite-derived classification maps to improve post-stratified forest parameter estimates is well established.When reducing the variance of post-stratification estimates for forest change parameters such as forest growth, it is logical to use a cha...

While several data sets for evaluating thematic fit of verb-role-filler triples exist, they do not control for verb polysemy. Thus, it is unclear how verb polysemy affects human ratings of thematic fit and how best to model that. We present a new dataset of human ratings on high vs. low-polysemy verbs matched for verb frequency, together with high vs. low-frequency and well-fitting vs. poorly-f...