Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a ...

Purpose. Text documents are an important source of data for tech mining techniques. Usually text databases include document sufficiently long to apply conventional text mining techniques. However in some tech mining tasks, such as capabilities identification process, we have database with very short texts, which represent a challenge for conventional text mining techniques. The problem has to d...

This paper presents a text-mining approach in order to extract candidate terms from a corpus. The relevant candidates are selected using a web-mining approach. The terms (i.e. relevant candidate terms) we find are the instances of specialized ontologies built during this process. The experiments are based on real data – Human Resources corpus – and they show the quality of our text and web mini...

The POSBIOTM/W1 is a workbench for machine-learning oriented biomedical text mining system. The POSTBIOTM/W is intended to assist biologist in mining useful information efficiently from biomedical text resources. To do so, it provides a suit of tools for gathering, managing, analyzing and annotating texts. The workbench is implemented in Java, which means that it is platform-independent.

In many applications, there is often a need for comparing multiple text collections to find commonalities and differences in topical themes, a task we refer to as comparative text mining. In this paper, we present a general comparative mining system (CTMS). The CTMS system takes any two collections of text and generates a list of cross-collection themes and their associated individual collectio...

In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content...

The extraction of nested, semantically rich relationships of biological entities has recently gained popularity in the biomedical text mining community. To move toward this objective, a method is proposed for reconstructing original semantic relationship graphs from projections, where each node and edge is mapped to the representative of its equivalence class, by determining the relationship ar...

An association rule in data mining is an implication of the form X Y where X is a set of antecedent items and Y is the consequent item. For years researchers have developed many tools to visualize association rules. However, few of these tools can handle more than dozens of rules, and none of them can effectively manage rules with multiple antecedents. Thus, it is extremely difficult to visuali...

Text mining has become a popular field with the rapid development of information technology and extensive amounts unstructured text data such as web pages, social network sites technical documentations. This contains lot information, which is extremely difficult to deal huge number various forms. Extracting analysing important from massive for example in automotive industries our major problem....