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.
form of an ontology which represents the distinct areas of Software Engineering knowledge inspired by SWEBOK (Software Engineering Body of Knowledge). Finally, the process of the classification of texts within the ontology is carried out in three steps: keyword analysis, processing of the document. We believe our proposal
use of the system. The soccer videos are very suitable for our framework, since it is easy to find Web-cast match reports for soccer games. The annotated videos are stored in MPEG-7 format in an object-oriented database. The keyword-based indexing allows fast retrieval of video segments. The system accepts match reports
engines are keyword-matching mechanism-based, and the existing full-text query search engines are inadequate at retrieving relevant information from various oral queries. With only predefined words and sentence-based recommendations, a social robot may not suggest the correct items, if items retrieved along with the
in an electronic health record (EHR) system, keyword search within the chart may produce many results that are not relevant or that may overlook related expressions and concepts entirely. In addition, some medical events, such as the occurrence of symptoms, are associated with important attributes such as location or
comprises of several components; (1) using a Stemming algorithm for text processing, (2) Formal Concept Analysis for dynamic extraction of keywords, (3) Ontology based concept extraction, (4)Google API is used to query the Google Image Database and extract the required multimedia elements, which are then mapped accordingly. A
Artificial Intelligence and web when amalgamated, it may produce miracle in terms of semantic web. E-learning works efficiently only when E-Content preparation is need based, searchable through semantic similarity between keywords. This paper describes a e-content/e-book preparation from existing available contents on
It has become common to search necessary services and contents using the Internet, but it is difficult to find exactly what one is looking for through keywords as each service is described in just too many ways. We developed "laddering" search service system that matches the needs of the users with the search targets
new Ontology-based Information Extraction (OBIE) system that extends existing systems in order to enrich and validate an ontology. Our model enables the ontology to find related recent knowledge in the domain from communities, by exploiting their underlying knowledge as keywords. The knowledge extraction process uses
from these data collections. KeyGraph is a word co-occurrence based algorithm for topic modeling. We provide an extension for KeyGraph algorithm by incorporating WordNet hypernyms for Keywords in the data collection. Our results show that incorporating hypernyms for KeyGraph algorithm would result improved topic and
difficulty due to the large size of the list of words in a thesaurus. In this paper, we present a new method for solving the problem of text categorization over a corpus of newspaper articles where the annotation must be composed of thesaurus elements. The method consists of applying lemmatization, obtaining keywords and named
In this paper we discuss the fundamental problem of information retrieval on the Web. Information on the Web is not semantically categorized and stored. This research focuses on applying semantic capabilities using ontology on search engine. By using ontology, search engine can search keywords that are conceptually
Web page recommendation model traces userspsila Web-surfing trails, extracts the useful information including keywords, Web page URLs and userspsila evaluations on Web pages, and automatically generates FCA (formal concept analysis) knowledge base and enterprise ontology knowledge base with WordNet. While users are
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.