The Syllabus Based Web Content Extractor (SBWCE)

Syllabus Based Web Content Extractor (SBWCE) introduces a new technique of Syllabus Based Web Content Mining. It makes the Syllabus Based Web Content Extraction easy and creates an instant online book view based on the links relevant to the given Syllabus. Three important contributions are made by the current work. First, as multiple format educational information is needed for Syllabus based content; the technique used makes the finding of such content easier. Second, a new approach for capturing and recording the heuristics involved during searching by experts is used. Third, the grouping of Syllabus Words for precise extraction is exploited. This paper introduces SBWCE and presents the related details

A Framework For Evaluating Information Quality Of Persian Weblogs

The World Wide Web is a great tool for exploring all kinds of information. Unlike books and journals, most of this information is unfiltered, i.e. not subject to editing or peer review by experts. This lack of quality control and the large increase in number of web sites make the task of finding quality information on the web especially critical. Meanwhile, new facilities for producing web pages such as weblogs make this issue more significant because Blogs are simple content management tools that enable non-experts to build easily updatable web diaries or online journals. Despite a decade of active research, a comprehensive methodology for the assessment of Information Quality (IQ) is lacking. Specifically, no framework for measuring information quality on the weblogs is currently available.After identifying and prioritizing IQ criteria on Weblogs, a Weblog management system that automatically calculates and collects IQ scores for created Weblogs is developed. The system is implemented on Persian Weblogs. Results of analysis of data collected by the Weblog management system show that there are significant correlations between many of the information quality variables. In addition, an analysis of the data revealed seven IQ dimensions on the Weblogs. Each of the dimensions was comprised of related IQ variables. Coefficients are identified for each variable in order to facilitate IQ measurement on the Weblogs. Moreover, statistical analysis shows that three specific sub-criteria for Weblogs; namely the number of written comments, number of received comments and comment per entry influence information quality on the Weblogs and interestingly fall into same dimension

Incorporating the position of sharing action in predicting popular videos in online social networks

LNCS v.8787 entitled: Web Information Systems Engineering - WISE 2014: 15th International Conference, Thessaloniki, Greece, October 12-14, 2014, Proceedings, Part 2Predicting popular videos in online social networks (OSNs) is important for network traffic engineering and video recommendation. In order to avoid the difficulty of acquiring all OSN users’ activities, recent studies try to predict popular media contents in OSNs only based on a very small number of users, referred to as experts. However, these studies simply treat all users’ diffusion actions as the same. Based on large-scale video diffusion traces collected from a popular OSN, we analyze the positions of users’ video sharing actions in the propagation graph, and classify users’ video sharing actions into three different types, i.e., initiator actions, spreader actions and follower actions. Surprisingly, while existing studies mainly focus on the initiators, our empirical studies suggest that the spreaders actually play a more important role in the diffusion process of popular videos. Motivated by this finding, we account for the position information of sharing actions to select initiator experts, spreader experts and follower experts, based on corresponding sharing actions. We conduct experiments on the collected dataset to evaluate the performance of these three types of experts in predicting popular videos. The evaluation results demonstrate that the spreader experts can not only make more accurate predictions than initiator experts and follower experts, but also outperform the general experts selected by existing studies.postprin

Searching Ontologies Based on Content: Experiments in the Biomedical Domain

As more ontologies become publicly available, finding the "right" ontologies becomes much harder. In this paper, we address the problem of ontology search: finding a collection of ontologies from an ontology repository that are relevant to the user's query. In particular, we look at the case when users search for ontologies relevant to a particular topic (e.g., an ontology about anatomy). Ontologies that are most relevant to such query often do not have the query term in the names of their concepts (e.g., the Foundational Model of Anatomy ontology does not have the term "anatomy" in any of its concepts' names). Thus, we present a new ontology-search technique that helps users in these types of searches. When looking for ontologies on a particular topic (e.g., anatomy), we retrieve from the Web a collection of terms that represent the given domain (e.g., terms such as body, brain, skin, etc. for anatomy). We then use these terms to expand the user query. We evaluate our algorithm on queries for topics in the biomedical domain against a repository of biomedical ontologies. We use the results obtained from experts in the biomedical-ontology domain as the gold standard. Our experiments demonstrate that using our method for query expansion improves retrieval results by a 113%, compared to the tools that search only for the user query terms and consider only class and property names (like Swoogle). We show 43% improvement for the case where not only class and property names but also property values are taken into account

Improving the Effectiveness and Efficiency of Web-Based Search Tasks for Policy Workers

We adapt previous literature on search tasks for developing a domain-specific search engine that supports the search tasks of policy workers. To characterise the search tasks we conducted two rounds of interviews with policy workers at the municipality of Utrecht, and found that they face different challenges depending on the complexity of the task. During simple tasks, policy workers face information overload and time pressures, especially during web-based searches. For complex tasks, users prefer finding domain experts within their organisation to obtain the necessary information, which requires a different type of search functionality. To support simple tasks, we developed a web search engine that indexes web pages from authoritative sources only. We tested the hypothesis that users prefer expert search over web search for complex tasks and found that supporting complex tasks requires integrating functionality that enables finding internal experts within the broader web search engine. We constructed representative tasks to evaluate the proposed system’s effectiveness and efficiency, and found that it improved user performance. The search functionality developed could be standardised for use by policy workers in different municipalities within the Netherlands

Improving the effectiveness and efficiency of web-based search tasks for policy workers

We adapt previous literature on search tasks for developing a domain-specific search engine that supports the search tasks of policy workers. To characterise the search tasks we conducted two rounds of interviews with policy workers at the municipality of Utrecht, and found that they face different challenges depending on the complexity of the task. During simple tasks, policy workers face information overload and time pressures, especially during web-based searches. For complex tasks, users prefer finding domain experts within their organisation to obtain the necessary information, which requires a different type of search functionality. To support simple tasks, we developed a web search engine that indexes web pages from authoritative sources only. We tested the hypothesis that users prefer expert search over web search for complex tasks and found that supporting complex tasks requires integrating functionality that enables finding internal experts within the broader web search engine. We constructed representative tasks to evaluate the proposed system’s effectiveness and efficiency, and found that it improved user performance. The search functionality developed could be standardised for use by policy workers in different municipalities within the Netherlands

DEVELOPING WEB-BASED ONLINE TEST SYSTEM TO BOOST IELTS ACADEMIC READING SCORE

Abstract: Web technology provides rich resources for both educators and learners in English teaching and learning process. In this context, the study aims at developing web-based online test for IELTS academic reading test on the users need for learners and educator of Universitas Darussalam Gontor. Addressing the issue of online test developing, this study utilized Alessi and Trollip instructional system design model. The formative evaluation and the increase in the average score at the pre-test and post-test of the learning motivation included alpha testing validated by two material and media experts and beta testing on learners’ attitude toward the online test, while summative evaluation covered learning outcomes. Upon analysis, the finding demonstrated that: (1) the resulting website: https://gets.unida.gontor.ac.id/pertanyaan/quiz was able to provide online evaluation for assessing reading performance among learners; (2) the increase in the average score on the pre-test and post-test of the learning outcomes of all learners was 0.43 (moderate category) and learner motivation scale was 0.38 (Medium-g courses). Hence, web-based online test could optimize learners’ excitement to assess their IELTS proficiency

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

Development of Learning Media for Introductory Information and Communication Technology Courses

This research aims at: (1) finding out the learning conditions in Introduction to Technology of Information and Communication course of Electrical Engineering Education Department at Makassar State University; (2) finding out the developmental phases of learning media based on web learning in Introduction to Technology of Information and Communication course of Electrical Engineering Education at Makassar State University; and (3) finding out the validity level of learning media based on material and media experts' assessment. This research employed a development research using ADDIE which is modified in three phases that is Analyze, Design, and Develop. The research is conducted at Electrical Engineering Education Department at Makassar State University. The informants were chosen from material and media experts. In line with that, the data was obtained through observation and questionnaires, while technique of data analysis through descriptive analysis. The results of this study show three developmental phases of learning media based on web learning in Introduction to Technology of Information and Communication course of Electrical Engineering Education Department at Universitas Negeri Makassar as follows: (1) analyze phase; (2) design phase; and (3) develop phase. The results of the validator (1) validation by material experts achieving the feasibility of 82.81%, (2) by the design experts who reached 89.58% from the results of the study of learning media in Introduction to Technology of Information and Communication that are developing Electronics so as to produce excellent results for this company. The conclusion is that this research uses Research and Development (R&D