EnTagRec: An Enhanced Tag Recommendation System for Software Information Sites

Software engineers share experiences with modern technologies by means of software information sites, such as STACK OVERFLOW. These sites allow developers to label posted content, referred to as software objects, with short descriptions, known as tags. However, tags assigned to objects tend to be noisy and some objects are not well tagged. To improve the quality of tags in software information sites, we propose ENTAGREC, an automatic tag recommender based on historical tag assignments to software objects and we evaluate its performance on four software information sites, STACK OVERFLOW, ASK UBUNTU, ASK DIFFERENT, and FREECODE. We observe that that ENTAGREC achieves Recall@5 scores of 0.805, 0.815, 0.88 and 0.64, and Recall@10 scores of 0.868, 0.876, 0.944 and 0.753, on STACK OVERFLOW, ASK UBUNTU, ASK DIFFERENT, and FREECODE, respectively. In terms of Recall@5 and Recall@10, averaging across the 4 datasets, ENTAGREC improves TAGCOMBINE, which is the state of the art approach, by 27.3% and 12.9% respectively

Modeling Tag Prediction based on Question Tagging Behavior Analysis of CommunityQA Platform Users

In community question-answering platforms, tags play essential roles in effective information organization and retrieval, better question routing, faster response to questions, and assessment of topic popularity. Hence, automatic assistance for predicting and suggesting tags for posts is of high utility to users of such platforms. To develop better tag prediction across diverse communities and domains, we performed a thorough analysis of users' tagging behavior in 17 StackExchange communities. We found various common inherent properties of this behavior in those diverse domains. We used the findings to develop a flexible neural tag prediction architecture, which predicts both popular tags and more granular tags for each question. Our extensive experiments and obtained performance show the effectiveness of our modelComment: 20 page

Knowledge management and Discovery for advanced Enterprise Knowledge Engineering

2012 - 2013The research work addresses mainly issues related to the adoption of models, methodologies and knowledge management tools that implement a pervasive use of the latest technologies in the area of Semantic Web for the improvement of business processes and Enterprise 2.0 applications. The first phase of the research has focused on the study and analysis of the state of the art and the problems of Knowledge Discovery database, paying more attention to the data mining systems. The most innovative approaches which were investigated for the "Enterprise Knowledge Engineering" are listed below. In detail, the problems analyzed are those relating to architectural aspects and the integration of Legacy Systems (or not). The contribution of research that is intended to give, consists in the identification and definition of a uniform and general model, a "Knowledge Enterprise Model", the original model with respect to the canonical approaches of enterprise architecture (for example with respect to the Object Management - OMG - standard). The introduction of the tools and principles of Enterprise 2.0 in the company have been investigated and, simultaneously, Semantic Enterprise based appropriate solutions have been defined to the problem of fragmentation of information and improvement of the process of knowledge discovery and functional knowledge sharing. All studies and analysis are finalized and validated by defining a methodology and related software tools to support, for the improvement of processes related to the life cycles of best practices across the enterprise. Collaborative tools, knowledge modeling, algorithms, knowledge discovery and extraction are applied synergistically to support these processes. [edited by author]XII n.s

Tag Recommendation in Software Information Sites

Abstract—Nowadays, software engineers use a variety of online media to search and become informed of new and interesting technologies, and to learn from and help one another. We refer to these kinds of online media which help software engineers im-prove their performance in software development, maintenance and test processes as software information sites. It is common to see tags in software information sites and many sites allow users to tag various objects with their own words. Users increasingly use tags to describe the most important features of their posted contents or projects. In this paper, we propose TagCombine, an automatic tag recommendation method which analyzes objects in software in-formation sites. TagCombine has 3 different components: 1. multi-label ranking component which considers tag recommendation as a multi-label learning problem; 2. similarity based rankin

Multimedia Development of English Vocabulary Learning in Primary School

In this paper, we describe a prototype of web-based intelligent handwriting education system for autonomous learning of Bengali characters. Bengali language is used by more than 211 million people of India and Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. This research project was aimed to develop an intelligent Bengali handwriting education system. As an intelligent tutor, the system can automatically check the handwriting errors, such as stroke production errors, stroke sequence errors, stroke relationship errors and immediately provide a feedback to the students to correct themselves. Our proposed system can be accessed from smartphone or iPhone that allows students to do practice their Bengali handwriting at anytime and anywhere. Bengali is a multi-stroke input characters with extremely long cursive shaped where it has stroke order variability and stroke direction variability. Due to this structural limitation, recognition speed is a crucial issue to apply traditional online handwriting recognition algorithm for Bengali language learning. In this work, we have adopted hierarchical recognition approach to improve the recognition speed that makes our system adaptable for web-based language learning. We applied writing speed free recognition methodology together with hierarchical recognition algorithm. It ensured the learning of all aged population, especially for children and older national. The experimental results showed that our proposed hierarchical recognition algorithm can provide higher accuracy than traditional multi-stroke recognition algorithm with more writing variability

In Pursuit of Recognition in a Digitally Divided City: Conceptualizing voice, visibility and presence in the age of social media

With social media’s increasing importance in modern society, this thesis investigates its role in the digital economy and how it shapes the everyday lives of Sheffield’s residents. The significance of social media ties, transactional relationships and concepts about how new media functions in the public sphere are interwoven throughout the literature review. Digital interactivity is conceived as a process, which in turn, influences the perception of status, reputation and recognition. Qualitative interviews were conducted with participants from each of the following three cohorts: computer learners, knowledge workers and global elites. An interactivity spectrum was developed after participant interviews emphasised how social media usage related to employment prospects. This spectrum evaluates the cohort’s online interactivities based on the following categories: technology and data linkages; networking and engagement; representation and identity; information awareness and sociability. This conceptual framework draws on usage patterns and investigates the social ties forged through digital connections. Interactivity serves to amplify voice and visibility; thus, online presence becomes an active form of social capital incorporating both visibility and voice. These cases suggest how digital interactivity and social capital accumulation may be theorized using voice, visibility and presence on the social media sites of Facebook, Twitter and LinkedIn. The three groups (learners, knowledge workers and elites) strive separately to achieve both local and national forms of recognition within the public sphere and are clearly marked out by their differences in social media interactivity. This research is important as it delineates a social capital creation pathway that begins with digital engagement and ends with social capital accumulation. The connection between engagement and capital creation also compels a rethink of the digital divide in light of new participatory media practices

Academic attitudes to new media in UK higher education: an interdisciplinary study

This thesis examines the attitudes of UK academics toward new media as both cultural artefacts and tools, assessing the relationship of those attitudes to traditionally distinct disciplinary structures. An inclusive and conceptually informed framework was developed following a review of multi-disciplinary literatures addressing the organisation of disciplines, the management of Higher Education, and the multiple meanings of new media. The original contribution of the thesis is an enriched understanding of what new media mean to academics both symbolically and practically at a time of immense technological and organisational change. Empirical data were gathered from a sample of 209 UK academics in four academic fields which were selected strategically using a frame based on the work of Whitley (2000). The primary instrument used was a self-administered online questionnaire (distributed to 953 individuals in 112 in-scope institutions, hence the response rate is 22 percent) using Likert scales and semantic differentials to capture attitudinal statements. Illustrative, descriptive and inferential statistics were computed from this, although it must be noted that the population size could only be estimated. An analysis of commonalities and differences in emerging and conventional disciplinary structures suggests a stronger influence of the practical rather than symbolic influences of discipline on academics' attitudes toward new media. A homogenisation of attitudes is found across not only disciplines, but genders, age groups, and experience levels. At the same time, while these findings echo those of other research, strong conceptual and methodological differences remain evident in debates about new media in much scholarly literature, primarily that drawn along disciplinary lines, or for a specialist audience. This suggests two equally important positions from which academics assess new media; those rooted in disciplinary modes, and those common to multiple practitioners and audiences in the academic 'workspace'. This can be seen as symptomatic of the new managerial models for research, teaching and assessment currently prevalent within HE

BOBCATSSS 2016 : Information, Libraries, Democracy. Proceedings & Abstracts

Actes du congrès BOBCATSSS 2016 qui s\u27est déroulé à Lyon du 27 au 29 janvier 2016 sur le thème : Information, bibliothèques, démocratie