An infrastructure for building semantic web portals

In this paper, we present our KMi semantic web portal infrastructure, which supports two important tasks of semantic web portals, namely metadata extraction and data querying. Central to our infrastructure are three components: i) an automated metadata extraction tool, ASDI, which supports the extraction of high quality metadata from heterogeneous sources, ii) an ontology-driven question answering tool, AquaLog, which makes use of the domain specific ontology and the semantic metadata extracted by ASDI to answers questions in natural language format, and iii) a semantic search engine, which enhances traditional text-based searching by making use of the underlying ontologies and the extracted metadata. A semantic web portal application has been built, which illustrates the usage of this infrastructure

The Best Answers? Think Twice: Online Detection of Commercial Campaigns in the CQA Forums

In an emerging trend, more and more Internet users search for information from Community Question and Answer (CQA) websites, as interactive communication in such websites provides users with a rare feeling of trust. More often than not, end users look for instant help when they browse the CQA websites for the best answers. Hence, it is imperative that they should be warned of any potential commercial campaigns hidden behind the answers. However, existing research focuses more on the quality of answers and does not meet the above need. In this paper, we develop a system that automatically analyzes the hidden patterns of commercial spam and raises alarms instantaneously to end users whenever a potential commercial campaign is detected. Our detection method integrates semantic analysis and posters' track records and utilizes the special features of CQA websites largely different from those in other types of forums such as microblogs or news reports. Our system is adaptive and accommodates new evidence uncovered by the detection algorithms over time. Validated with real-world trace data from a popular Chinese CQA website over a period of three months, our system shows great potential towards adaptive online detection of CQA spams.Comment: 9 pages, 10 figure

Language technologies and the evolution of the semantic web

The availability of huge amounts of semantic markup on the Web promises to enable a quantum leap in the level of support available to Web users for locating, aggregating, sharing, interpreting and customizing information. While we cannot claim that a large scale Semantic Web already exists, a number of applications have been produced, which generate and exploit semantic markup, to provide advanced search and querying functionalities, and to allow the visualization and management of heterogeneous, distributed data. While these tools provide evidence of the feasibility and tremendous potential value of the enterprise, they all suffer from major limitations, to do primarily with the limited degree of scale and heterogeneity of the semantic data they use. Nevertheless, we argue that we are at a key point in the brief history of the Semantic Web and that the very latest demonstrators already give us a glimpse of what future applications will look like. In this paper, we describe the already visible effects of these changes by analyzing the evolution of Semantic Web tools from smart databases towards applications that harness collective intelligence. We also point out that language technology plays an important role in making this evolution sustainable and we highlight the need for improved support, especially in the area of large-scale linguistic resources

A Survey on Data-Driven Evaluation of Competencies and Capabilities Across Multimedia Environments

The rapid evolution of technology directly impacts the skills and jobs needed in the next decade. Users can, intentionally or unintentionally, develop different skills by creating, interacting with, and consuming the content from online environments and portals where informal learning can emerge. These environments generate large amounts of data; therefore, big data can have a significant impact on education. Moreover, the educational landscape has been shifting from a focus on contents to a focus on competencies and capabilities that will prepare our society for an unknown future during the 21st century. Therefore, the main goal of this literature survey is to examine diverse technology-mediated environments that can generate rich data sets through the users’ interaction and where data can be used to explicitly or implicitly perform a data-driven evaluation of different competencies and capabilities. We thoroughly and comprehensively surveyed the state of the art to identify and analyse digital environments, the data they are producing and the capabilities they can measure and/or develop. Our survey revealed four key multimedia environments that include sites for content sharing & consumption, video games, online learning and social networks that fulfilled our goal. Moreover, different methods were used to measure a large array of diverse capabilities such as expertise, language proficiency and soft skills. Our results prove the potential of the data from diverse digital environments to support the development of lifelong and lifewide 21st-century capabilities for the future society

Review Paper on Answers Selection and Recommendation in Community Question Answers System

Nowadays, question answering system is more convenient for the users, users ask question online and then they will get the answer of that question, but as browsing is primary need for each an individual, the number of users ask question and system will provide answer but the computation time increased as well as waiting time increased and same type of questions are asked by different users, system need to give same answers repeatedly to different users. To avoid this we propose PLANE technique which may quantitatively rank answer candidates from the relevant question pool. If users ask any question, then system provide answers in ranking form, then system recommend highest rank answer to the user. We proposing expert recommendation system, an expert will provide answer of the question which is asked by the user and we also implement sentence level clustering technique in which a single question have multiple answers, system provide most suitable answer to the question which is asked by the user

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance

Content quality assessment related frameworks for social media

The assessment of content quality (CQ) in social media adds a layer of complexity over traditional information quality assessment frameworks. Challenges arise in accurately evaluating the quality of content that has been created by users from different backgrounds, for different domains and consumed by users with different requirements. This paper presents a comprehensive review of 19 existing CQ assessment related frameworks for social media in addition to proposing directions for framework improvements

Development and validation of an integrated model for evaluating e-service quality, usability and user experience (e-SQUUX) of Web-based applications in the context of a University web portal

Text in EnglishDevelopments in Internet technology and pervasive computing over the past two and half decades have resulted in a variety of Web-based applications (WBAs) that provide products and services to online users or customers. The Internet is used not only to transfer information via the web but is increasingly used to provide electronic services including business transactions, information-delivery and social networking, as well as e-government, e-health and e-learning. For such organisations, e-service quality, usability and user experience are considered to be critical determinants of their products’ or services’ success. Many studies to model these three concepts separately have been undertaken as part of broader studies of software quality or service quality modelling. However, to the current researcher’s knowledge, none of the studies have focussed on proposing an evaluation model that integrates and combines the three of them. This research is an effort to fill that gap. The primary purpose of this mixed-methods research was to develop a conceptual integrated model for evaluating e-service quality, usability and user experience (e-SQUUX) of WBAs and then contextualise it to evaluation of a University web portal (UWP). This was undertaken using an exploratory sequential research design. During a qualitative phase, an extensive extensive systematic literature review of 264 relevant sources relating to dimensions of e-service quality, usability and user experience, was undertaken to derive an integrated conceptual e-service quality, usability and user experience (e-SQUUX) Model for evaluating WBAs. The model was then empirically refined through a sequential series of validations, thus developing various versions of the e-SQUUX Model. First, it was content validated by a set of four expert reviewers. Second, during the quantitative phase, in the context of a University web portal, a questionnaire survey was conducted that included a comprehensive pilot study with 29 partipants, prior to the main survey. The main survey data from 174 particiapants was used to determine a validated model, using Exploratory factor analysis (EFA), followed by producing a structural model, using partial least square – structural equation modelling (PLS-SEM). This version consisted of the components of the final e-SQUUX Model. Consequently, the research enriches the body of knowledge on IS and HCI by providing the e-SQUUX Model as an evaluation tool. For designers, developers and managers of UWPs, the model serves as a customisable set of evaluation criteria and also provides specific recommendations for design. In line with the Exploratory sequential design of mixed methods research, the findings of the qualitative work in this research influenced the subsequent quantitative study, since the potential Likert-scale questionnaire items were derived from the definitions and meanings of the components that emanated from the qualitative phase of the study. Consequently, this research is an exemplar for developing an integrated evaluation model for specific facets or domains, and of its application in a particular context, in this case, a University web portal. Keywords: e-service quality, usability, user experience, evaluation model, integrated model, exploratory factor analysis, partial least square – structural equation modelling (PLS-SEM), mixed methods research, Exploratory sequential design, quantitative study, qualitative study, validation, Web-based applications, University web portalInformation SystemPh D. (Information Systems