Knowledgebase Representation for Royal Bengal Tiger In The Context of Bangladesh

Royal Bengal Tiger is one of the penetrating threaten animal in Bangladesh forest at Sundarbans. In this work we have had concentrate to establish a robust Knowledgebase for Royal Bengal Tiger. We improve our previous work to achieve efficiency on knowledgebase representation. We have categorized the tigers from others animal from collected data by using Support Vector Machines(SVM) .Manipulating our collected data in a structured way by XML parsing on JAVA platform. Our proposed system generates n-triple by considering parsed data. We proceed on an ontology is constructed by ProtE9;gE9; which containing information about names, places, awards. A straightforward approach of this work to make the knowledgebase representation of Royal Bengal Tiger more reliable on the web. Our experiments show the effectiveness of knowledgebase construction. Complete knowledgebase construction of Royal Bengal Tigers how the efficient out-put. The complete knowledgebase construction helps to integrate the raw data in a structured way. The outcome of our proposed system contains the complete knowledgebase. Our experimental results show the strength of our system by retrieving information from ontology in reliable way

Natural language querying for video databases

Cataloged from PDF version of article.The video databases have become popular in various areas due to the recent advances in technology. Video archive systems need user-friendly interfaces to retrieve video frames. In this paper, a user interface based on natural language processing (NLP) to a video database system is described. The video database is based on a content-based spatio-temporal video data model. The data model is focused on the semantic content which includes objects, activities, and spatial properties of objects. Spatio-temporal relationships between video objects and also trajectories of moving objects can be queried with this data model. In this video database system, a natural language interface enables flexible querying. The queries, which are given as English sentences, are parsed using link parser. The semantic representations of the queries are extracted from their syntactic structures using information extraction techniques. The extracted semantic representations are used to call the related parts of the underlying video database system to return the results of the queries. Not only exact matches but similar objects and activities are also returned from the database with the help of the conceptual ontology module. This module is implemented using a distance-based method of semantic similarity search on the semantic domain-independent ontology, WordNet. (C) 2008 Elsevier Inc. All rights reserved

Метод контекстного пошуку на основі тезаурусу предметної області

The creation of the intellectual search engine was reviewed based on the domain thesaurus. Text linguistics was taken as the example of domain. The approach to the creation of semantic metrics was suggested based on such a thesaurus. For this aim the weights of importances of the groups relations were introduced between the thesaurus terms (synonyms, correlates, holonyms, meronyms, hyperonyms). The thesaurus was converted into the weighted conceptual graph. Based on Floyd-Warshall algorithm the distances between the terms of weighted conceptual graph were found. Those distances were used during the intellectual search of relevant text documents based on the key words. If some key words are not mentioned in the text document, the search engine looks for the most related term to the searched one. The efficiency of the proposed approach was introduced in comparison to other methods.В статье предложен подход к построению семантической метрики на основе тезауруса предметной области. Описан процесс построения такого тезауруса. Предложено использовать построенную таким образом базу знаний для поиска потенциальных партнеров, которые занимаются подобными научными проблемами в предметной области для которой построен тезаурус.У статті запропоновано підхід до побудови семантичної метрики на основі тезаурусу предметної області. Описано процес побудови такого тезаурусу. Запропоновано використати побудовану таким чином базу знань для пошуку потенційних партнерів, які займаються подібними науковими проблемами в предметній області для якої побудовано тезаурус

Exploring diseases based biomedical document clustering and visualization using self-organizing maps

Document clustering is a text mining technique used to provide better document search and browsing in digital libraries or online corpora. In this research, a vector representation of concepts of diseases and similarity measurement between concepts are proposed. They identify the closest concepts of diseases in the context of a corpus. Each document is represented by using the vector space model. A weight scheme is proposed to consider both local content and associations between concepts. Self-Organizing Maps (SOM) are often used as document clustering algorithm. The vector projection and visualization features of SOM enable visualization and analysis of the cluster distribution and relationships on the two dimensional space. The Davies-Bouldin index is used to validate the clusters based on the visualized cluster distributions. The results show that the proposed document clustering framework generates meaningful clusters and can facilitate clustering visualization and information retrieval based on the concepts of diseases

METHOD OF AUTOMATED DEVELOPMENT AND EVALUATION OF ONTOLOGIES’ QUALITIES OF KNOWLEDGE BASES

The process of automated development of base ontology is considered. It has been offered to consider the concepts and elements of ontologies for increasing the effectiveness of knowledge bases, the core of which is the ontology. Methods of specifying the weights of the relevant elements and optimization the structure of knowledge base of ontologies has been elaborated. It has been offered to evaluate the quality of the ontologies based on ISO 9126

COMPUTER SYSTEM FOR AUTOMATED ONTOLOGY BUILDING BASIC CROCUS

The article exposes the approach developing a computer system of automated ontology building based on creation of architecture system ontology synthesis CROCUS (Cognition Relations or Concepts Using Semantics) software model. The basic modules of the system and its operations are described. The choice of software tools for implementation was described. Example of SDK decision for system realization was substantiated. The using of this system allows filling the domain ontology in automatic mode

Fuzzy ontology representation using OWL 2

AbstractThe need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing a procedure to represent such information within current standard languages and tools. In this work, we follow the latter approach, by identifying the syntactic differences that a fuzzy ontology language has to cope with, and by proposing a concrete methodology to represent fuzzy ontologies using OWL 2 annotation properties. We also report on some prototypical implementations: a plug-in to edit fuzzy ontologies using OWL 2 annotations and some parsers that translate fuzzy ontologies represented using our methodology into the languages supported by some reasoners

Natural language querying for video databases

The video databases have become popular in various areas due to the recent advances in technology. Video archive systems need user-friendly interfaces to retrieve video frames. In this paper, a user interface based on natural language processing (NLP) to a video database system is described. The video database is based on a content-based spatio-temporal video data model. The data model is focused on the semantic content which includes objects, activities, and spatial properties of objects. Spatio-temporal relationships between video objects and also trajectories of moving objects can be queried with this data model. In this video database system, a natural language interface enables flexible querying. The queries, which are given as English sentences, are parsed using link parser. The semantic representations of the queries are extracted from their syntactic structures using information extraction techniques. The extracted semantic representations are used to call the related parts of the underlying video database system to return the results of the queries. Not only exact matches but similar objects and activities are also returned from the database with the help of the conceptual ontology module. This module is implemented using a distance-based method of semantic similarity search on the semantic domain-independent ontology, WordNet. © 2008 Elsevier Inc. All rights reserved