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Web search engine provides information for the submitted query of the users, without consideration of user's interests. Personalized Web search is used to consider the user interests for providing the results. Existing research Link-click-concept based ranking (LC2R) algorithm is suggested that extracts a user's conceptual preferences from users' click through data resulted from web search. This preference...
The research project we present in this paper concerns an ontology-based recommender for teacher training and support. An important issue in Computer-Assisted Language Learning education is the complexity of exploiting technology in order to enhance language teaching. The integration of technology into language education is a rather complex achievement, which implies the ability to understand the...
The paper proposes a new scheme named as WPP (Web Page Personalization) for effective web page recommendations. WPP consist of page hit count, total time spent in every link, number of downloads and link separation. Based on these parameters the personalization has been proposed. The system proposes a new implicit user feedback and event link access schemes for effective web page customization along...
Quickly moving to an unfamiliar field for researchers is painful due to a mass of scientific articles to study without knowing their research contents. Research point and its implementation method are two helpful aspects. However these two aspects are difficult to be achieved without appropriate semantic tools. This paper proposes a literature search framework which supports a new perspective retrieval...
This research proposes Dual-Spiral methodology, a knowledgebase construction methodology to process the diverse and complex queries about common sense. The main idea of the methodology is that humans and machines collaborate each other to create the knowledgebase of good quality. By applying to WiseKB project, we verify how the methodology works effectively.
E-commerce has become a major fact that affects the rapid development of the global economy for past few decades. With the growth of the information technology sector, internet and the mobile phone usage have increased greatly, which prompts retailers to attract more and more consumers to their shopping malls. As retailers tend to reach and keep the constant interaction, consumers no longer feel a...
This paper builds upon the BWEC1 (Business for Women in Women of Emerging Country) research project to improve the socio-economic situation of handicraft women. In this project our principal task is to build data warehouse schema from handicraft women social network. For that, we follow a semi-supervised clustering-based methodology. In this paper, we propose the adaptation of a semi-supervised hierarchical...
The competition inherent to globalisation has led enterprises to gather in nests of specialised business providers with the purpose of building better applications and provide more complete solutions. This, added to the improvements on the Information and Communications Technologies (ICT), led to a paradigm shift from product-centrism to service-centrism and to the need to communicate and interoperate...
In many technical domains, the generic problem-solving knowledge is scarce even hough a large number of concrete resolutions exist and are well documented. This makes the machine learning from resolution traces approach facing a number of challenges, not least among them the complexity of the underlying domain (concepts, relationships, events, processes, etc.) and the machine-readability of the documented...
Usually, documents are given in textual form, accompanied by a set of terminological classifications (metadata), based on vocabularies of domain ontologies. This paper presents a novel method for advancing the above classification, by extracting more properties of the analyzed documents. We first extract additional roles from the textual part and together with roles extracted from the ontology statements,...
People are using social media to a greater extent, particularly in emergency situations. However, approaches for processing and analyzing the vast quantities of data produced currently lag far behind. In this paper we discuss important steps, and the associated challenges, for processing and analyzing social media in emergencies. In our research project EmerGent, a huge volume of low-quality messages...
The Qur'an is the religious text of Islam, distinguished by its miraculous style, it is considered as the basic reference for all Islamic sciences, and therefore it's very sensitive to model its content for fear to make bad assumptions and axioms. In recent years a number of researches has been done to facilitate the retrieval of knowledge from the Qur'an, but most of the available researches are...
In this paper, a comparison between two different text extraction methods is given, namely the linguistic (Part-of-Speech / POS) and statistical methods (Term Frequency Inverse Document Frequency / TF-IDF). Text extractions were performed as part of ontology population in the Indonesian tourism domain. This paper also contributes in creating a multimedia corpus from three different resources or websites...
Complex networks of direct relevance to biomedicine have not yet been fully mapped largely due to the incompleteness, isolation, and heterogeneity of data. The Semantic Web, by providing a technical framework for the integration and sharing of heterogeneous databases in different domains, can potentially enable more effective complex network mapping and analysis. However, the feasibility of using...
The paper objectives are twofold: to discuss the essence and challenges of automatic ontology design as applied to the Big data semantic modeling and to present Semantic Concept Analysis (SCA), a framework specifically developed for automatic actionable ontology design in Big data scenario. This framework integrates the data-driven DBpedia-based technology for semi-automatic design of the ontology...
With the widespread growth of social networking there are several online forums that are dedicated to discussing health and well-being. These forums are great resources for collecting patient and health related information, as people tend to freely share and discuss their health conditions and treatments with others having similar experiences. There are several methods available for extracting data...
In this article we present three similarity measures based on ontologies that are used to allow data mining in case of very sparse data. With the use of semantic knowledge associated to data sources we can aggregate data from similar sources and use that aggregated data to train a machine learning model. This article focuses on the ontology-based similarity measures that are required to compare data...
It is an area of text classification which continues gives contribution in research field and it analyse and classify the user generated data like reviews, blogs and comments etc. In opinion mining customer reviews generally contain the product opinions of many customers expressed in various forms consisting natural sentences. A common phenomenon in natural sentence-based customer reviews is that...
Our aim is to extract information about literary characters in unstructured texts. We employ natural language processing and reasoning on domain ontologies. The first task is to identify the main characters and the parts of the story where these characters are described or act. We illustrate the system in a scenario in the folktale domain. The system relies on a folktale ontology that we have developed...
In the age of Big Data, which is clearly affecting also the Healthcare sector, one of the most valuable challenge is the one connected with the information extraction from raw data that implies the automatic detection of significant facts in unstructured texts and their transformation into structured documents, which are indexable and queryable exactly like databases. The volume, variety, velocity,...
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