Text summarization is machine based generation of a shortened version of a text. The summary should be a non-redundant extract from the original text. Most researches of text summarization use sentence extraction instead of abstraction to produce a summary. Extraction is depending mainly on sentences that already contained in the original input, which makes it more accurate and more concise. Wh...

In last years, multi-agent systems (MAS) have achieved a remarkable success and diffusion in employment for distributed and complex applications. A fundamental contribution has come by the adoption of reuse techniques and tools providing a strong support during the design phase. Even though design patterns have been widely accepted by industrial and academic organizations as a proper technique ...

Software patterns are computing artifacts used to document knowledge that may be reused during software development process. There are several types of patterns, such as analysis, design, and architectural, among others. Design patterns are the most well known by designers, but many of them are described in books and scientific papers, a recurring way of documenting patterns that limits their r...

The paper presents a framework for introducing design patterns that facilitate or improve the techniques used during ontology lifecycle. Some distinctions are drawn between kinds of ontology design patterns. Some contentoriented patterns are presented in order to illustrate their utility at different degrees of abstraction, and how they can be specialized or composed. The proposed framework and...

Design patterns are a valuable mechanism to capture and disseminate best practice in software design. The oft-cited definition of an Alexandrian pattern, ′′a solution to a problem in a context”, stimulates the definition of patterns from knowledge and expertise in any domain. Indeed, their application has spread from the object-oriented community, who first adopted them, through different softw...

Current approaches of hypernymy acquisition are mostly based on syntactic or surface representations and extract hypernymy relations between surface word forms and not word readings. In this paper we present a purely semantic approach for hypernymy extraction based on semantic networks (SNs). This approach employs a set of patterns sub0(a1, a2) ← premise where the premise part of a pattern is g...

This paper represents initial work on corpus methods for acquiring lexical/semantic pattern lexicons for text understanding. Recently, implementors of information extraction (IE) systems have moved away from using conventional syntactic parsing methods, instead adopting a variety of pattern based approaches for complex IE tasks. While there has been much work towards automated acquisition of le...

Most existing approaches to Twitter sentiment analysis assume that sentiment is explicitly expressed through affective words. Nevertheless, sentiment is often implicitly expressed via latent semantic relations, patterns and dependencies among words in tweets. In this paper, we propose a novel approach that automatically captures patterns of words of similar contextual semantics and sentiment in...

This paper presents a method for unsupervised discovery of semantic patterns. Semantic patterns are useful for a variety of text understanding tasks, in particular for locating events in text for information extraction. The method builds upon previously described approaches to iterative unsupervised pattern acquisition. One common characteristic of prior approaches is that the output of the alg...

Open-class semantic lexicon induction is of great interest for current knowledge harvesting algorithms. We propose a general framework that uses patterns in bootstrapping fashion to learn open-class semantic lexicons for different kinds of relations. These patterns require seeds. To estimate the goodness (the potential yield) of new seeds, we introduce a regression model that considers the conn...