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Question Answering (QA) system is the task where arbitrary question IS posed in the form of natural language statements and a brief and concise text returned as an answer. Contrary to search engines where a long list of relevant documents returned as a result of a query, QA system aims at providing the direct answer or passage containing the answer. We propose a general purpose question answering...
This paper proposes an approach to finding answers within single text for a given question through extracting a network of categories from Wikipedia as background knowledge to support matching between question and answer. Experiments show that the approach is effective for keyword-based QA.
This paper proposed a textual entailment classification system developed based on a dataset focusing on individual entailment-related linguistic phenomena. Identical and synonymous terms in the text pair were aligned and ignored. Several groups of classification rules have been proposed with respect to the difference between the sentences in the text pair. The set of Wikipedia redirected titles became...
Exploratory search is cumbersome with today's search engines, where a user aims to better understand complex concepts. Query expansions techniques have been widely used in exploratory search. However, query expansions often recommend queries that differ from the user's search intentions due to different contexts. Yet, many of users' needs could be addressed by asking people via popular Community Question...
The characteristic of poor information of short text often makes the effect of traditional keywords extraction not as good as expected. In this paper, we propose a graph-based ranking algorithm by exploiting Wikipedia as an external knowledge base for short text keywords extraction. To overcome the shortcoming of poor information of short text, we introduce the Wikipedia to enrich the short text....
The problem of entity resolution is widely studied in the research community, where the goal is to identify real users associated with the user references in the documents. We focus on the problem of entity resolution in dyadic data, where associations between one pair of domain entities such as documents-words and associations between another pair, such as documents-users are observed, the example...
Investigating learning performance predictors is an important part of the educational process. Active participation or engagement is one such predictor, which has been widely analyzed in traditional learning settings, but less in the emerging social-media based learning environments. This paper explores the relationship between students' active participation on three social media tools (wiki, blog,...
This paper presents an approach to build multilayer cognitive maps, and gives an example of utilization. In the modeled of a problem using cognitive maps, it is possible the utilization of several cognitive maps, where each one expresses a different aspect (knowledge) of the problem, but which must be interlinked. That is, a multilayer cognitive map can enrich the modeling of a system, with the flow...
With the rapid development ot biomedical sciences, a growing amount of papers reporting new scientific findings are published and indexed in different unstructured biomedical data sources. In order to really appreciate and effectively benefit from the availability of this amount of data there is an urgent need to support the deployment of intelligent information services, such as: temporal trends...
The growing number of users in microblogging sites such as Twitter has created the problem of searching useful followees among millions of users in a reasonable time. One way to address this problem is using a recommender system, which is aimed at providing a list of useful followees in a reasonable time. Although Twitter provides a functionality what it calls ‘Who to Follow’, neither is it configurable...
With the rapid development of the Internet, more and more people use social networks to share information and express their views, which lead to a vigorous growth of information. How to select useful and interesting information for users, that is user topic interest, gets more and more attention. Tag functionality in microblog can get user topic interests easily and achieve information recommendation...
With the ever expanding mobile device ecosystem, mobile users face a vast and constantly growing application pool. At the same time, in our daily life, waiting occurs regularly at different places such as shopping centers, where mobile applications become the de facto means to consume the time periods. In this paper, we propose a novel application recommendation system that utilizes human activity...
Applying machine learning algorithms for detecting vandalism in two languages are described in this paper. Vandalism is a major issue in Wikipedia as it accounts for about 1% of edits during 2015. The majority of vandalism is from human editors, whose vandalism can be traced through access and edit logs. In this paper, we propose using a list of classifiers in one language, and then evaluate them...
Some of the greatest challenges for Software requirements elicitation are related with the identification of what is needed to be developed and with the understanding of the organization business rules. In this context, this paper aims to suggest the use of Comic Books in the process of requirements elicitation within a business model and evaluate the results of applying this technique. To reach this...
The number of entities in large-scale knowledge bases has been growing in recent years. The key issue to entity linking using a knowledge base such as Wikipedia is entity disambiguation. The objective of our proposing system is to disambiguate entities in documents and link entity mentions to their corresponding Wikipedia articles. To this end, our system ranks the set of candidate entities based...
Nowadays, Wikipedia has become one of the most important tools for searching information. Since its long articles are taking time to read, as well as section titles are sometimes too short to capture comprehensive summarization, we aim at extracting informative phrases that readers can refer to. Existing work on topic labelling works effectively and performs well on document categorization, but inadequate...
With the rapid evolution of Linked Open Data (LOD), researchers are exploiting it to solve particular problems such as semantic similarity assessment. Existing LOD-based semantic similarity approaches attach compared data (terms or concepts) to LOD resources to exploit their semantic descriptions and relationships with other resources and estimate the degree of overlap between resources. Current approaches...
Lecture videos constitute an important part of the e-learning paradigm. These online video-lectures contain multimedia materials aimed at explaining complex concepts in a more effective way. The videos are mostly grouped by their subjects. However, often there are overlaps between the subjects, e.g. Mathematics and Statistics. Hence, educational content-wise, some of the lecture videos can belong...
We present a freely available dataset of multimedia material that can be used to build enriched browsing and retrieval systems for music. It is one result of the EU-FP7 funded project “Performances as Highly Enriched aNd Interactive Concert experiences” (PHENICX) that aims at enhancing the listener experience when enjoying classical music. The presented PHENICX-SMM dataset includes in total more than...
The personalization of TV viewing has evolved, along with the proliferation of TV program content provided through various means, to become a key issue in future TV systems. It has thus become important to construct personalized user profiles for use in recommending TV programs in order to effectively personalize TV viewing. We have developed a method for automatically constructing a user profile...
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