The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
keyword driven crawling with relevancy decision mechanism and uses Ontology concepts which ensures the best path for improving crawler's performance. This paper introduces extraction of URLs based on keyword or search criteria. It extracts URLs for web pages which contains searched keyword in their content and considers such
Artificial Intelligence and web when amalgamated, it may produce miracle in terms of semantic web and its one of the important application is in E-Learning. E-learning works efficiently only when E-Content preparation is need based, customizable and on-demand, preparation is real-time, searchable through keyword/s
suggest the ways that make and renew the ontology, which are related with the keywords that users input in the search engine, automatically for the automatic generation of ontology that is not limited by specific domain. Input keyword and relation keywords become OWL, and the relation among the created OWL is expressed by
The core task of digital library is that provides good information retrieval system for the users. Traditional information retrieval technology is mainly based on keyword matching and has little semantic inferring ability. Moreover it does not provide semantic guidance for users. So information retrieval system may
This paper is started from addressing the common automatic method of ontology construction. Then, from viewpoint of the military intelligent processing, the two-level domain ontology architecture is designed. One level is the keyword ontology. The other level is the instance ontology. Different level has different
Today's Environment, Web contributes greatly to the creation of an ever-increasing global information database. Web is a collection of billions of web pages. Web 2.0 is purely based on keyword based searching. Because of using keyword based search engine, people may get relevant or irrelevant information. The amount
This paper aims to design a system model that analyzes the unstructured data inside the posts about electronic products on social networking websites. For the purposes of this study, posts on social networking websites have been mined and the keywords are extracted from such posts. The extracted keywords and the
The current grid information retrieval commonly uses the method based on keywords, and the retrieval method depends on the keywords that match their participation in the external form of characters, rather than the concept expressed by their neglect of the semantic information inherent in the word. It brings about
proposing a Scheme to search information semantically over unstructured P2P network, based on ontology. The ontology best described as a formal representation of a set of words within a domain and a relationship between those words rather keywords. The ontology uses Dewey Decimal Code to facilitate the classification taxonomy
Conventional document clustering techniques are mainly based on the existence of keywords and the number of occurrences of it. Most of the term frequency based clustering techniques consider the documents as bag-of-words and ignore the important relationships between the words in the document. Phrase based clustering
Traditional Web Service search methodology dependant on keywords is time consuming and inefficient. The search results are often inexact. The substantive reason is that, the description of Web Service lacks semantic information. Search Engines can't accomplish the communication automatically and intelligently between
analyzer to pick up information of service and use keywords to find out related services; then we cluster Web services according to the similarity of services; last, we select the appropriate Web service from list of services.
Traditionally information retrieval consists mainly of determining which documents of a collection contain the keywords in the user query. However, a growing number of tasks, especially those related to Semantic Web technologies and applications rely on accurately measuring the similarity between documents and online
Because of ignoring the semantic information inside the keywords, the traditional searching engine based on the key words has low recall and precision. Aiming at this, some semantic retrieval system design ideas and the retrieval process are proposed in this paper.The key technologies-related in semantic retrieval
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.