Search results for: semantic search.

Authors: R. Babisaraswathi, N. Shanthi, S. S. Kiruthika

Abstract:

Web search engines are designed to retrieve and extract the information in the web databases and to return dynamic web pages. The Semantic Web is an extension of the current web in which it includes semantic content in web pages. The main goal of semantic web is to promote the quality of the current web by changing its contents into machine understandable form. Therefore, the milestone of semantic web is to have semantic level information in the web. Nowadays, people use different keyword- based search engines to find the relevant information they need from the web. But many of the words are polysemous. When these words are used to query a search engine, it displays the Search Result Records (SRRs) with different meanings. The SRRs with similar meanings are grouped together based on Word Sense Disambiguation (WSD). In addition to that semantic annotation is also performed to improve the efficiency of search result records. Semantic Annotation is the process of adding the semantic metadata to web resources. Thus the grouped SRRs are annotated and generate a summary which describes the information in SRRs. But the automatic semantic annotation is a significant challenge in the semantic web. Here ontology and knowledge based representation are used to annotate the web pages.

Keywords: Ontology, Semantic Web, WordNet, Word Sense Disambiguation.

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Authors: Martin Dostal, Dalibor Fiala, Karel Ježek

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In this paper we would like to introduce some of the best practices of using semantic markup and its significance in the success of web applications. Search engines are one of the best ways to reach potential customers and are some of the main indicators of web sites' fruitfulness. We will introduce the most important semantic vocabularies which are used by Google and Yahoo. Afterwards, we will explain the process of semantic markup implementation and its significance for search engines and other semantic markup consumers. We will describe techniques for slow conceiving RDFa markup to our web application for collecting Call for papers (CFP) announcements.

Keywords: Call for papers, Google, RDFa, semantic markup, semantic web, Yahoo.

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Authors: Nhon Do, Thuong Huynh, An Pham

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Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.

Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.

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Authors: Hikmat A. M. Abd-El-Jaber, Tengku M. T. Sembok

Abstract:

The information on the Web increases tremendously. A number of search engines have been developed for searching Web information and retrieving relevant documents that satisfy the inquirers needs. Search engines provide inquirers irrelevant documents among search results, since the search is text-based rather than semantic-based. Information retrieval research area has presented a number of approaches and methodologies such as profiling, feedback, query modification, human-computer interaction, etc for improving search results. Moreover, information retrieval has employed artificial intelligence techniques and strategies such as machine learning heuristics, tuning mechanisms, user and system vocabularies, logical theory, etc for capturing user's preferences and using them for guiding the search based on the semantic analysis rather than syntactic analysis. Although a valuable improvement has been recorded on search results, the survey has shown that still search engines users are not really satisfied with their search results. Using ontologies for semantic-based searching is likely the key solution. Adopting profiling approach and using ontology base characteristics, this work proposes a strategy for finding the exact meaning of the query terms in order to retrieve relevant information according to user needs. The evaluation of conducted experiments has shown the effectiveness of the suggested methodology and conclusion is presented.

Keywords: information retrieval, user profiles, semantic Web, ontology, search engine.

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Authors: Frederike Ohrem, Lukas Sikorski, Bastian Haarmann

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Often the users of a semantic search application are facing the problem that they do not find appropriate terms for their search. This holds especially if the data to be searched is from a technical field in which the user does not have expertise. In order to support the user finding the results he seeks, we developed a domain-specific ontology and implemented it into a search application. The ontology serves as a knowledge base, suggesting technical terms to the user which he can add to his query. In this paper, we present the search application and the underlying ontology as well as the project EnArgus in which the application was developed.

Keywords: Information system, knowledge representation, ontology, semantic search.

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Authors: A. Ismail, M. S. Joy, J. E. Sinclair, M. I. Hamzah

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This paper focuses on a novel method for semantic searching and retrieval of information about learning materials. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. A novel metametadata taxonomy has been developed which provides the basis for a semantic search engine to extract, match and map queries to retrieve relevant results. The use of ontological views is a foundation for viewing the pedagogical content of metadata extracted from learning objects by using the pedagogical attributes from the metametadata taxonomy. Using the ontological approach and metametadata (based on the metametadata taxonomy) we present a novel semantic searching mechanism.These three strands – the taxonomy, the ontological views, and the search algorithm – are incorporated into a novel architecture (OMESCOD) which has been implemented.

Keywords: Metadata, metametadata, semantic, ontologies.

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Authors: K. Venkateswari, U. K. Balaji Saravanan, K. Thangaraj, K. V. Deepana

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Image search engines rely on the surrounding textual keywords for the retrieval of images. It is a tedious work for the search engines like Google and Bing to interpret the user’s search intention and to provide the desired results. The recent researches also state that the Google image search engines do not work well on all the images. Consequently, this leads to the emergence of efficient image retrieval technique, which interprets the user’s search intention and shows the desired results. In order to accomplish this task, an efficient image re-ranking framework is required. Sequentially, to provide best image retrieval, the new image re-ranking framework is experimented in this paper. The implemented new image re-ranking framework provides best image retrieval from the image dataset by making use of re-ranking of retrieved images that is based on the user’s desired images. This is experimented in two sections. One is offline section and other is online section. In offline section, the reranking framework studies differently (reference classes or Semantic Spaces) for diverse user query keywords. The semantic signatures get generated by combining the textual and visual features of the images. In the online section, images are re-ranked by comparing the semantic signatures that are obtained from the reference classes with the user specified image query keywords. This re-ranking methodology will increases the retrieval image efficiency and the result will be effective to the user.

Keywords: CBIR, Image Re-ranking, Image Retrieval, Semantic Signature, Semantic Space.

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Authors: Lilac A. E. Al-Safadi

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With the advance of multimedia and diagnostic images technologies, the number of radiographic images is increasing constantly. The medical field demands sophisticated systems for search and retrieval of the produced multimedia document. This paper presents an ongoing research that focuses on the semantic content of radiographic image documents to facilitate semantic-based radiographic image indexing and a retrieval system. The proposed model would divide a radiographic image document, based on its semantic content, and would be converted into a logical structure or a semantic structure. The logical structure represents the overall organization of information. The semantic structure, which is bound to logical structure, is composed of semantic objects with interrelationships in the various spaces in the radiographic image.

Keywords: Semantic Indexing, Content-Based Retrieval, Radiographic Images, Data Model

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Authors: Quratulain N. Rajput, Sajjad Haider, Nasir Touheed

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The internet has become an attractive avenue for global e-business, e-learning, knowledge sharing, etc. Due to continuous increase in the volume of web content, it is not practically possible for a user to extract information by browsing and integrating data from a huge amount of web sources retrieved by the existing search engines. The semantic web technology enables advancement in information extraction by providing a suite of tools to integrate data from different sources. To take full advantage of semantic web, it is necessary to annotate existing web pages into semantic web pages. This research develops a tool, named OWIE (Ontology-based Web Information Extraction), for semantic web annotation using domain specific ontologies. The tool automatically extracts information from html pages with the help of pre-defined ontologies and gives them semantic representation. Two case studies have been conducted to analyze the accuracy of OWIE.

Keywords: Ontology, Semantic Annotation, Wrapper, Information Extraction.

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Authors: Karim Heidari

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Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. At the present time, only human beings are able to understand the product information published online. The emerging semantic Web technologies have the potential to deeply influence the further development of the Internet Economy. In this paper we propose a scenario based research approach to predict the effects of these new technologies on electronic markets and business models of traders and intermediaries and customers. Over 300 million searches are conducted everyday on the Internet by people trying to find what they need. A majority of these searches are in the domain of consumer ecommerce, where a web user is looking for something to buy. This represents a huge cost in terms of people hours and an enormous drain of resources. Agent enabled semantic search will have a dramatic impact on the precision of these searches. It will reduce and possibly eliminate information asymmetry where a better informed buyer gets the best value. By impacting this key determinant of market prices semantic web will foster the evolution of different business and economic models. We submit that there is a need for developing these futuristic models based on our current understanding of e-commerce models and nascent semantic web technologies. We believe these business models will encourage mainstream web developers and businesses to join the “semantic web revolution."

Keywords: E-Commerce, E-Business, Semantic Web, XML.

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Authors: Guang-Ho Cha

Abstract:

This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.

Keywords: Context-sensitive search, image search, media search, similarity ranking, similarity search.

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Authors: Jorge Cardoso

Abstract:

It has been recognized that due to the autonomy and heterogeneity, of Web services and the Web itself, new approaches should be developed to describe and advertise Web services. The most notable approaches rely on the description of Web services using semantics. This new breed of Web services, termed semantic Web services, will enable the automatic annotation, advertisement, discovery, selection, composition, and execution of interorganization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the semantic Web. It describes how semantic Web services extend Web services as the semantic Web improves the current Web, and presents three different conceptual approaches to deploying semantic Web services, namely, WSDL-S, OWL-S, and WSMO.

Keywords: Semantic Web, Web service, Web process, WWW

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Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias, Hany T. Alashwal, Rohayanti Hassan, FarhanMohamed

Abstract:

The most important property of the Gene Ontology is the terms. These control vocabularies are defined to provide consistent descriptions of gene products that are shareable and computationally accessible by humans, software agent, or other machine-readable meta-data. Each term is associated with information such as definition, synonyms, database references, amino acid sequences, and relationships to other terms. This information has made the Gene Ontology broadly applied in microarray and proteomic analysis. However, the process of searching the terms is still carried out using traditional approach which is based on keyword matching. The weaknesses of this approach are: ignoring semantic relationships between terms, and highly depending on a specialist to find similar terms. Therefore, this study combines semantic similarity measure and genetic algorithm to perform a better retrieval process for searching semantically similar terms. The semantic similarity measure is used to compute similitude strength between two terms. Then, the genetic algorithm is employed to perform batch retrievals and to handle the situation of the large search space of the Gene Ontology graph. The computational results are presented to show the effectiveness of the proposed algorithm.

Keywords: Gene Ontology, Semantic similarity measure, Genetic algorithm, Ontology search

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-ofthe- art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents.

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking.

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Authors: Fereshteh Mahdavi, Maizatul Akmar Ismail, Noorhidawati Abdullah

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Currently WWW is the first solution for scholars in finding information. But, analyzing and interpreting this volume of information will lead to researchers overload in pursuing their research. Trend detection in scientific publication retrieval systems helps scholars to find relevant, new and popular special areas by visualizing the trend of input topic. However, there are few researches on trend detection in scientific corpora while their proposed models do not appear to be suitable. Previous works lack of an appropriate representation scheme for research topics. This paper describes a method that combines Semantic Web and ontology to support advance search functions such as trend detection in the context of scholarly Semantic Web system (SSWeb).

Keywords: Trend, Semi-Automatic Trend Detection, Ontology, Semantic Trend Detection.

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Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller

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This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.

Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.

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Authors: K. K. Yong, R. Mahmud, C. S. Woo

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Data mining and knowledge engineering have become a tough task due to the availability of large amount of data in the web nowadays. Validity and reliability of data also become a main debate in knowledge acquisition. Besides, acquiring knowledge from different languages has become another concern. There are many language translators and corpora developed but the function of these translators and corpora are usually limited to certain languages and domains. Furthermore, search results from engines with traditional 'keyword' approach are no longer satisfying. More intelligent knowledge engineering agents are needed. To address to these problems, a system known as Multilingual Word Semantic Network is proposed. This system adapted semantic network to organize words according to concepts and relations. The system also uses open source as the development philosophy to enable the native language speakers and experts to contribute their knowledge to the system. The contributed words are then defined and linked using lexical and semantic relations. Thus, related words and derivatives can be identified and linked. From the outcome of the system implementation, it contributes to the development of semantic web and knowledge engineering.

Keywords: Multilingual, semantic network, intelligent knowledge engineering.

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Authors: Hoda Waguih

Abstract:

A serious problem on the WWW is finding reliable information. Not everything found on the Web is true and the Semantic Web does not change that in any way. The problem will be even more crucial for the Semantic Web, where agents will be integrating and using information from multiple sources. Thus, if an incorrect premise is used due to a single faulty source, then any conclusions drawn may be in error. Thus, statements published on the Semantic Web have to be seen as claims rather than as facts, and there should be a way to decide which among many possibly inconsistent sources is most reliable. In this work, we propose a trust model for the Semantic Web. The proposed model is inspired by the use trust in human society. Trust is a type of social knowledge and encodes evaluations about which agents can be taken as reliable sources of information or services. Our proposed model allows agents to decide which among different sources of information to trust and thus act rationally on the semantic web.

Keywords: Semantic Web, Trust, Web of Trust, WWW.

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Authors: N. Soussi, M. Bahaj

Abstract:

The enormous amount of information stored on the web increases from one day to the next, exposing the web currently faced with the inevitable difficulties of research pertinent information that users really want. The problem today is not limited to expanding the size of the information highways, but to design a system for intelligent search. The vast majority of this information is stored in relational databases, which in turn represent a backend for managing RDF data of the semantic web. This problem has motivated us to write this paper in order to establish an effective approach to support semantic transformation algorithm for SPARQL queries to SQL queries, more precisely SPARQL SELECT queries; by adopting this method, the relational database can be questioned easily with SPARQL queries maintaining the same performance.

Keywords: RDF, Semantic Web, SPARQL, SPARQL Query Transformation, SQL.

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Authors: Jorge Cardoso

Abstract:

Semantic Web services will enable the semiautomatic and automatic annotation, advertisement, discovery, selection, composition, and execution of inter-organization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. There is a growing consensus that Web services alone will not be sufficient to develop valuable solutions due the degree of heterogeneity, autonomy, and distribution of the Web. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the Semantic Web. It presents the synergies that can be created between Web Services and Semantic Web technologies to provide a new generation of eservices.

Keywords: Semantic Web, Web service, Web process, WWW.

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Authors: Haytham Al-Feel, M.A.Koutb, Hoda Suoror

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There are many problems associated with the World Wide Web: getting lost in the hyperspace; the web content is still accessible only to humans and difficulties of web administration. The solution to these problems is the Semantic Web which is considered to be the extension for the current web presents information in both human readable and machine processable form. The aim of this study is to reach new generic foundation architecture for the Semantic Web because there is no clear architecture for it, there are four versions, but still up to now there is no agreement for one of these versions nor is there a clear picture for the relation between different layers and technologies inside this architecture. This can be done depending on the idea of previous versions as well as Gerber-s evaluation method as a step toward an agreement for one Semantic Web architecture.

Keywords: Semantic Web Architecture, XML, RDF and Ontology.

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Authors: Karim Heidari, Serajodin Katebi, Ali Reza Mahdavi Far

Abstract:

The purpose of this paper is to study Database Models to use them efficiently in E-commerce websites. In this paper we are going to find a method which can save and retrieve information in Ecommerce websites. Thus, semantic web applications can work with, and we are also going to study different technologies of E-commerce databases and we know that one of the most important deficits in semantic web is the shortage of semantic data, since most of the information is still stored in relational databases, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF. To achieve this goal we study XML structures for relational data bases of old websites and eventually we will come up one level over XML and look for a map from relational model (RDM) to RDF. Noting that a large number of semantic webs get advantage of relational model, opening the ways which can be converted to XML and RDF in modern systems (semantic web) is important.

Keywords: E-Commerce, Semantic Web, Database, XML, RDF.

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: Building information modeling, elemental graph data model, geometric and topological data models, and graph theory.

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Authors: Sahar Nasrolahi, Mahdi Nikdast, Mehrdad Mahdavi Boroujerdi

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The purpose of semantic web research is to transform the Web from a linked document repository into a distributed knowledge base and application platform, thus allowing the vast range of available information and services to be more efficiently exploited. As a first step in this transformation, languages such as OWL have been developed. Although fully realizing the Semantic Web still seems some way off, OWL has already been very successful and has rapidly become a defacto standard for ontology development in fields as diverse as geography, geology, astronomy, agriculture, defence and the life sciences. The aim of this paper is to classify key concepts of Semantic Web as well as introducing a new practical approach which uses these concepts to outperform Word Wide Web.

Keywords: Semantic Web, Ontology, OWL, Microformat, Word Wide Web.

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Authors: S. Housseno, A. Simonet, M. Simonet

Abstract:

Semantic query optimization consists in restricting the search space in order to reduce the set of objects of interest for a query. This paper presents an indexing method based on UB-trees and a static analysis of the constraints associated to the views of the database and to any constraint expressed on attributes. The result of the static analysis is a partitioning of the object space into disjoint blocks. Through Space Filling Curve (SFC) techniques, each fragment (block) of the partition is assigned a unique identifier, enabling the efficient indexing of fragments by UB-trees. The search space corresponding to a range query is restricted to a subset of the blocks of the partition. This approach has been developed in the context of a KB-DBMS but it can be applied to any relational system.

Keywords: Index, Range query, UB-tree, Space Filling Curve, Query optimization, Views, Database, Integrity Constraint, Classification.

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Authors: S. Logeswari, K. Premalatha

Abstract:

Search is the most obvious application of information retrieval. The variety of widely obtainable biomedical data is enormous and is expanding fast. This expansion makes the existing techniques are not enough to extract the most interesting patterns from the collection as per the user requirement. Recent researches are concentrating more on semantic based searching than the traditional term based searches. Algorithms for semantic searches are implemented based on the relations exist between the words of the documents. Ontologies are used as domain knowledge for identifying the semantic relations as well as to structure the data for effective information retrieval. Annotation of data with concepts of ontology is one of the wide-ranging practices for clustering the documents. In this paper, indexing based on concept and annotation are proposed for clustering the biomedical documents. Fuzzy c-means (FCM) clustering algorithm is used to cluster the documents. The performances of the proposed methods are analyzed with traditional term based clustering for PubMed articles in five different diseases communities. The experimental results show that the proposed methods outperform the term based fuzzy clustering.

Keywords: MeSH Ontology, Concept Indexing, Annotation, semantic relations, Fuzzy c-means.

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Authors: Mohammad Yasrebi, Mehran Mohsenzadeh

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The third phase of web means semantic web requires many web pages which are annotated with metadata. Thus, a crucial question is where to acquire these metadata. In this paper we propose our approach, a semi-automatic method to annotate the texts of documents and web pages and employs with a quite comprehensive knowledge base to categorize instances with regard to ontology. The approach is evaluated against the manual annotations and one of the most popular annotation tools which works the same as our tool. The approach is implemented in .net framework and uses the WordNet for knowledge base, an annotation tool for the Semantic Web.

Keywords: Semantic Annotation, Metadata, Information Extraction, Semantic Web, knowledge base.

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Authors: Haluk Eren, Mucahit Karaduman

Abstract:

This paper presents 15-year trends for scientific studies in a scientific database considering 3D and vehicle words. Two words are selected to find their associated publications in IEEE scholar database. Both of keywords are entered individually for the years 2002, 2012, and 2016 on the database to identify the preferred subjects of researchers in same years. We have classified closer research fields after searching and listing. Three years (2002, 2012, and 2016) have been investigated to figure out progress in specified time intervals. The first one is assumed as the initial progress in between 2002-2012, and the second one is in 2012-2016 that is fast development duration. We have found very interesting and beneficial results to understand the scholars’ research field preferences for a decade. This information will be highly desirable in smart city-based research purposes consisting of 3D and vehicle-related issues.

Keywords: Vehicle, 3D, smart city, scholarly search, semantic.

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Authors: Visit Hirankitti, Vuong Tran Xuan

Abstract:

Multi-agent communication of Semantic Web information cannot be realized without the need to reason with ontology and agent locations. This is because for an agent to be able to reason with an external semantic web ontology, it must know where and how to access to that ontology. Similarly, for an agent to be able to communicate with another agent, it must know where and how to send a message to that agent. In this paper we propose a framework of an agent which can reason with ontology and agent locations in order to perform reasoning with multiple distributed ontologies and perform communication with other agents on the semantic web. The agent framework and its communication mechanism are formulated entirely in meta-logic.

Keywords: Semantic Web, agent communication, ontologies.

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Authors: Anna V. Zhdanova, Uwe Keller

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We summarize information that facilitates choosing an ontology language for knowledge intensive applications. This paper is a short version of the ontology language state-of-the-art and evolution analysis carried out for choosing an ontology language in the IST Esperonto project. At first, we analyze changes and evolution that took place in the filed of Semantic Web languages during the last years, in particular, around the ontology languages of the RDF/S and OWL family. Second, we present current trends in development of Semantic Web languages, in particular, rule support extensions for Semantic Web languages and emerging ontology languages such as WSMO languages.

Keywords: OWL, RDF/S, Semantic Web Languages, WSML

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