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As Wikipedia became the largest human knowledge repository, quality measurement of its articles received a lot of attention during the last decade. Most research efforts focused on classification of Wikipedia articles quality by using a different feature set. However, so far, no “golden feature set” was proposed. In this paper, we present a novel approach for classifying Wikipedia articles by analysing...
Wikipedia is the result of a collaborative effort aiming to represent human knowledge and to make it accessible for everyone. As such it contains lots of contemporary as well as history-related information. This research looks into historical data available in Wikipedia to explore its various time-related characteristics. In particular, we study Wikipedia articles on historical persons. Our analysis...
Organizational processes involving collaborating resources, such as development processes, innovation processes, and decision-making processes, typically affect the performance of many organizations. Moreover, including required but missing, resources and capabilities of collaborations can improve the performance of corresponding processes drastically. In this work, we demonstrate the extended Informal...
Nodos is a new project with the main goal to promote and build a comprehensive knowledge base of performing arts, artists, cultural groups & spaces, plays and festivals. The work of recording and preservation this kind of artistic expressions contributes to the preservation of the Intangible Cultural Heritage, as has been defined by UNESCO. One of the biggest challenges related to the recording...
Collaborative systems such as Wikipedia have taken an important step toward creating content and organizing knowledge. Because they allow all people involve in creating content, such systems will face vandals' attacks and challenges. Therefore, in order to use this encyclopedia, it is important to trust in its content and measure its quality. User's reputation is an important factor for trusting electronic...
Semantic web technology can influence the next generation of eLearning systems and applications. Ontology as a major component of semantic web can be used in creating metadata for eLearning resources to improve adaptive eLearning systems. This paper presents an approach to automatically enrich eLearning domain ontology based on the integration of graph clustering techniques and external knowledge...
The human visual system always focuses at a distinct depth. Therefore, objects that lie at different depths appear blurred, a phenomenon known as Depth of Field (DoF); as the user's focus depth changes, different objects come in and out of focus. Augmented Reality (AR) is a technology that superimposes computer graphics (CG) images onto a user's view of the real world. A commonly used AR display device...
Filling the gap between natural language expressions and ontology concepts or properties is the new trend in Semantic Web. Ontology lexicalization introduces a new layer of lexical information for ontology properties and concepts. We propose a method based on unsupervised learning for the extraction of the potential lexical expressions of DBpedia propertiesfrom Wikipedia text corpus. It is a resource-driven...
Wikipedia is an online encyclopedia which contains millions of articles related to different subject domains. Wikipedia also has a search page itself to display the links corresponding to Wikipedia articles for a given user query input. This search result page displays the search results according to the relevance order, without any content based grouping. This paper presents an experimental deduction...
Social Information Retrieval can be interpreted as querying the private information spaces of others within one's social network. One of the crucial steps in such a search approach is to identify the set of potential information providers to route the query to. In this experiment, we compare various routing mechanisms based on topic models (Latent Dirichlet Allocation, LDA), Explicit Semantic Analysis...
We evaluate the suitability of latent and explicit semantic spaces of documents for Information Retrieval (IR) tasks using a dataset obtained from the Q&A community Stackexchange. In addition, the ability of the latent semantic spaces to reconstruct human relevance judgments is explored. The latent semantic spaces are generated with Latent Dirichlet Allocation (LDA), while explicit semantic spaces...
This paper introduces the problem of topical sequence profiling. Given a sequence of text collections such as the annual proceedings of a conference, the topical sequence profile is the most diverse explicit topic embedding for that text collection sequence that is both representative and minimal. Topic embeddings represent a text collection sequence as numerical topic vectors by storing the relevance...
Literature recommender systems support users in filtering the vast and increasing number of documents in digital libraries and on the Web. For academic literature, research has proven the ability of citation-based document similarity measures, such as Co-Citation (CoCit), or Co-Citation Proximity Analysis (CPA) to improve recommendation quality. In this paper, we report on the first large-scale investigation...
General purpose Search Engines (SEs) crawl all domains (e.g., Sports, News, Entertainment) of the Web, but sometimes the informational need of a query is restricted to a particular domain (e.g., Medical). We leverage the work of SEs as part of our effort to route domain specific queries to local Digital Libraries (DLs). SEs are often used even if they are not the “best” source for certain types of...
In current education, it is difficult for a teacher to know the engagement of each student, the contents that students cannot understand and the reason why students cannot perform sufficiently in the quizzes and exams. To study student engagement in classroom, we digitize materials used in lectures, including textbooks and collect event logs of tablets used by students. By analyzing these logs, we...
Information Extraction is an important task in Natural Language Processing research. Named Entity Recognition as one of the basic tasks of information extraction, the effect has a great impact on the subsequent tasks such as Relation Extraction. And a major difficulty of NER lies in the unknown word identification. For this issue, method of exploiting Wikipedia external information methods was studied...
Quantifying the semantic relation between words is a key element in several applications including the treatments at the meaning level. A great variety of approaches are proposed in order to quantify the semantic proximity between concepts or words. These approaches exploit computational models including the hierarchical and textual information of the semantic resources. Among these models, the distributional...
Trolling describes a range of antisocial online behaviors that aim at disrupting the normal operation of online social networks and media. Combating trolling is an important problem in the online world. Existing approaches rely on human-based or automatic mechanisms for identifying trolls and troll posts. In this paper we take a novel approach to the trolling problem: our goal is to identify the targets...
Semantic relation plays an important role in knowledge acquisition research. This paper proposes a method of semantic relation acquisition and automatic synthesis based on Wikipedia. First of all, we obtain the three kinds of basic semantic relations from Wikipedia and extend the semantic of concept aiming at the problem of semantic fuzziness in the semantic relation. Then, an automatic synthesis...
Hyponymy is one of the most critical semantic relations, which contributes magnificently to semantic dictionary, information retrieval etc. In this paper, a method of extracting hyponymy is proposed based on multiple data sources fusion, which convert the extraction of hyponymy to the extraction of hypernyms for target words. First, mining candidate hypernyms for the target words based on search engine,...
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