Modeling naturalistic argumentation in research literatures:representation and interaction design issues

This article characterizes key weaknesses in the ability of current digital libraries to support scholarly inquiry, and as a way to address these, proposes computational services grounded in semiformal models of the naturalistic argumentation commonly found in research literatures. It is argued that a design priority is to balance formal expressiveness with usability, making it critical to coevolve the modeling scheme with appropriate user interfaces for argument construction and analysis. We specify the requirements for an argument modeling scheme for use by untrained researchers and describe the resulting ontology, contrasting it with other domain modeling and semantic web approaches, before discussing passive and intelligent user interfaces designed to support analysts in the construction, navigation, and analysis of scholarly argument structures in a Web-based environment. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 17–47, 2007.

Timeline generation with social attention

Timeline generation is an important research task which can help users to have a quick understanding of the overall evolution of any given topic. It thus attracts much attention from research communities in recent years. Nevertheless, existing work on timeline generation often ignores an important factor, the attention attracted to topics of interest (hereafter termed "social attention"). Without taking into consideration social attention, the generated timelines may not reflect users' collective interests. In this paper, we study how to incorporate social attention in the generation of timeline summaries. In particular, for a given topic, we capture social attention by learning users' collective interests in the form of word distributions from Twitter, which are subsequently incorporated into a unified framework for timeline summary generation. We construct four evaluation sets over six diverse topics. We demonstrate that our proposed approach is able to generate both informative and interesting timelines. Our work sheds light on the feasibility of incorporating social attention into traditional text mining tasks. Copyright © 2013 ACM.

What do people think about when they answer theory of planned behaviour questionnaires? A 'think aloud' study

Two studies aiming to identify the nature and extent of problems that people have when completing theory of planned behaviour (TPB) questionnaires, using a cognitive interviewing approach are reported. Both studies required participants to 'think aloud' as they completed TPB questionnaires about: (a) increasing physical activity (six general public participants); and (b) binge drinking (13 students). Most people had no identifiable problems with the majority of questions. However, there were problems common to both studies, relating to information retrieval and to participants answering different questions from those intended by researchers. Questions about normative influence were particularly problematic. The standard procedure for developing TPB questionnaires may systematically produce problematic questions. Suggestions are made for improving this procedure. Copyright © 2007 SAGE Publications.

Applying Genetic Algorithm In Query Improvement Problem

This paper presents an adaptive method using genetic algorithm to modify user’s queries, based on relevance judgments. This algorithm was adapted for the three well-known documents collections (CISI, NLP and CACM). The method is shown to be applicable to large text collections, where more relevant documents are presented to users in the genetic modification. The algorithm shows the effects of applying GA to improve the effectiveness of queries in IR systems. Further studies are planned to adjust the system parameters to improve its effectiveness. The goal is to retrieve most relevant documents with less number of non-relevant documents with respect to user's query in information retrieval system using genetic algorithm.

Development of the Combined Method for Designing Dataflow Systems

The methods of designing of information systems for large organizations are considered in the paper. The structural and object-oriented approaches are compared. For the practical realization of the automated dataflow systems the combined method for the system development and analysis is proposed.

Analysis of the Distributions of Color Characteristics in Art Painting Images

In this paper we study some of the characteristics of the art painting image color semantics. We analyze the color features of differ- ent artists and art movements. The analysis includes exploration of hue, saturation and luminance. We also use quartile’s analysis to obtain the dis- tribution of the dispersion of defined groups of paintings and measure the degree of purity for these groups. A special software system “Art Paint- ing Image Color Semantics” (APICSS) for image analysis and retrieval was created. The obtained result can be used for automatic classification of art paintings in image retrieval systems, where the indexing is based on color characteristics.

Learning higher-level features with convolutional restricted Boltzmann machines for sentiment analysis

In recent years, learning word vector representations has attracted much interest in Natural Language Processing. Word representations or embeddings learned using unsupervised methods help addressing the problem of traditional bag-of-word approaches which fail to capture contextual semantics. In this paper we go beyond the vector representations at the word level and propose a novel framework that learns higher-level feature representations of n-grams, phrases and sentences using a deep neural network built from stacked Convolutional Restricted Boltzmann Machines (CRBMs). These representations have been shown to map syntactically and semantically related n-grams to closeby locations in the hidden feature space. We have experimented to additionally incorporate these higher-level features into supervised classifier training for two sentiment analysis tasks: subjectivity classification and sentiment classification. Our results have demonstrated the success of our proposed framework with 4% improvement in accuracy observed for subjectivity classification and improved the results achieved for sentiment classification over models trained without our higher level features.

Algorithmic Minimization of Non-zero Entries in 0,1-Matrices

In this paper we present algorithms which work on pairs of 0,1- matrices which multiply again a matrix of zero and one entries. When applied over a pair, the algorithms change the number of non-zero entries present in the matrices, meanwhile their product remains unchanged. We establish the conditions under which the number of 1s decreases. We recursively define as well pairs of matrices which product is a specific matrix and such that by applying on them these algorithms, we minimize the total number of non-zero entries present in both matrices. These matrices may be interpreted as solutions for a well known information retrieval problem, and in this case the number of 1 entries represent the complexity of the retrieve and information update operations.

Position Paper: Improving Source Code Reuse through Documentation Standardization

In the context of Software Reuse providing techniques to support source code retrieval has been widely experimented. However, much effort is required in order to find how to match classical Information Retrieval and source code characteristics and implicit information. Introducing linguistic theories in the software development process, in terms of documentation standardization may produce significant benefits when applying Information Retrieval techniques. The goal of our research is to provide a tool to improve source code search and retrieval In order to achieve this goal we apply some linguistic rules to the development process.

Share.TEC Portal: How the Metadata Repositories of Educational Resources Meet the Users’ Expectations

This is an extended version of an article presented at the Second International Conference on Software, Services and Semantic Technologies, Sofia, Bulgaria, 11–12 September 2010.

Цифровите библиотеки в обучението на учители

Krassen Stefanov, Pavel Boytchev, Eliza Stefanova, Atanas Georgiev, Nikolina Nikolova, Alexander Grigorov - This paper discusses the role of the contemporary European digital libraries in teachers education. It presents a digital repository of metadata resources for teachers education, as well as a portal for the community of practices, build around the repository. Both the repository and the community are developed in the frame of the European project Share.TEC. The paper describes teachers’ and teachers educators’ expectations from the system. In addition, the adaptability model, on which the system is based on, and its realization in the portal are presented.

Online Access to the Encyclopaedia Slavica Sanctorum

Encyclopaedia Slavica Sanctorum project aims at building a repertoire of medieval and early modern Bulgarian texts for saints in combination with ethnological data and some visual sources. A basic project task is to produce an accessible on-line digital repository of this valuable cultural heritage treasure. The paper presents the Encyclopaedia Slavica Sanctorum environment, its architecture, functional specification, application modeling process and software implementation. The paper also discusses the specifics of the ―Encyclopaedia Slavica Sanctorum‖ project and its knowledge domain. The paper also presents the integration between the Encyclopaedia Slavica Sanctorum and the Bulgarian Iconographical Digital Library, a digital library keeping rare specimens, private collections of Orthodox icons, wall- paintings and other iconographical objects, selected from difficult-to-access storages, distant churches, chapels, and monasteries, objects in a risk environment or unstable conditions.

Research on Linguistic Approaches, Used for Semantic Explanation of Bell’s Knowledge

This paper presents a research of linguistic structure of Bulgarian bells knowledge. The idea of building semantic structure of Bulgarian bells appeared during the “Multimedia fund - BellKnow” project. In this project was collected a lots of data about bells, their structure, history, technical data, etc. This is the first attempt for computation linguistic explain of bell knowledge and deliver a semantic representation of that knowledge. Based on this research some linguistic components, aiming to realize different types of analysis of text objects are implemented in term dictionaries. Thus, we lay the foundation of the linguistic analysis services in these digital dictionaries aiding the research of kinds, number and frequency of the lexical units that constitute various bell objects.

Medieval Sources and Present-Day Folklore Materials on Saints in an Electronic Encyclopedia

This paper discusses the variety of the digitized content of an electronic encyclopedia on the veneration of saints according to Bulgarian sources. The emphasis is on medieval Slavonic Church manuscripts and on present-day records of Bulgarian folklore narratives and songs. The combination of these sources provokes discussion of the so-called folklore Christianity and adds new dimensions to the understanding of the role of the cults of saints for culture and of the religiosity of the Bulgarians.

Prospecção tecnológica para geração de energia eólica

The acceleration of technological change and the process of globalization has intensified competition and the need for new products (goods and services), resulting in growing concern for organizations in the development of technological, economic and social advances. This work presents an overview of the development of wind energy-related technologies and design trends. To conduct this research, it is (i) a literature review on technological innovation, technological forecasting methods and fundamentals of wind power; (ii) the analysis of patents, with the current technology landscape studied by means of finding information in patent databases; and (iii) the preparation of the map of technological development and construction of wind turbines of the future trend information from the literature and news from the sector studied. Step (ii) allowed the study of 25 644 patents between the years 2003-2012, in which the US and China lead the ranking of depositors and the American company General Electric and the Japanese Mitsubishi stand as the largest holder of wind technology. Step (iii) analyzed and identified that most of the innovations presented in the technological evolution of wind power are incremental product innovations to market. The proposed future trends shows that the future wind turbines tend to have a horizontal synchronous shaft, which with the highest diameter of 194m and 164m rotor nacelle top, the top having 7,5MW generation. The materials used for the blades are new materials with characteristics of low density and high strength. The towers are trend with hybrid materials, uniting the steel to the concrete. This work tries to cover the existing gap in the gym on the use of technological forecasting techniques for the wind energy industry, through the recognition that utilize the patent analysis, analysis of scientific articles and stories of the area, provide knowledge about the industry and influencing the quality of investment decisions in R & D and hence improves the efficiency and effectiveness of wind power generation