Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

MOOGLE: a metamodel-based model search engine

Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.

Web Scale Discovery Systems – How to assess the best solution

The University of São Paulo has been experiencing the increase in contents in electronic and digital formats, distributed by different suppliers and hosted remotely or in clouds, and is faced with the also increasing difficulties related to facilitating access to this digital collection by its users besides coexisting with the traditional world of physical collections. A possible solution was identified in the new generation of systems called Web Scale Discovery, which allow better management, data integration and agility of search. Aiming to identify if and how such a system would meet the USP demand and expectation and, in case it does, to identify what the analysis criteria of such a tool would be, an analytical study with an essentially documental base was structured, as from a revision of the literature and from data available in official websites and of libraries using this kind of resources. The conceptual base of the study was defined after the identification of software assessment methods already available, generating a standard with 40 analysis criteria, from details on the unique access interface to information contents, web 2.0 characteristics, intuitive interface, facet navigation, among others. The details of the studies conducted into four of the major systems currently available in this software category are presented, providing subsidies for the decision-making of other libraries interested in such systems.