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.
? Doesn't it understand it now? Google is very good at correcting typing mistakes, figuring out what I “meant” when I miss-typed a query or suggesting keyword to expand our search query. In this paper we redefine the idea of searching optimised information on the web using Capture-Recapture method. This paper
With the advent of Web 2.0, RESTful web services are becoming increasingly popular to emphasize the web as platform. There are already many RESTful web services and the number of services is increasing rapidly. Thus, it can be difficult to find specific services using keyword based retrieval. To solve this problem, a
The representation and organization of learning objects should provide the user with easy access to the information in which he or she is interested. Traditionally information retrieval systems support keyword-based searching where the search engine returns a set of documents (or links to the documents). In the
A new semantic search scheme for XML data is proposed. The semantics of both XML documents and the query are enriched by domain ontology annotation. Also, the additional information provided by the structure of XML documents is considered by adding node path index, semantic keyword index and element tag index to
Nowadays, with the appearance of more and more web services, it has been one of the key points that how to find the target service quickly and precisely. Traditional methods of web service discovery are only based on the keyword matching, but it's very difficult to realize more detailed and intelligent services, and
In the era of information explosion, information retrieval has become a bottleneck in information sharing and integration. However currently, the existing information retrieval methods are mainly based on keyword matching, which can not fully take advantage of the information context and potential knowledge. All of
of ontology-aware keyword search of XML documents with a particular focus on EMR XML documents. Our current prototypes and experiments use the health level seven (HL7) clinical document architecture (CDA) Release 2.0 standard of EMR representation and the systematized nomenclature of human and veterinary medicine
used to associate portions of the EMR document with concepts defined in a domain ontology. In this paper we present the XOntoRank system which tackles the problem of ontology-aware keyword search on XML documents with a particular focus on EMR XML documents. Our running examples and experiments use the Health Level Seven
Existing approaches to ontology retrieval solely base on keyword matching and return a lengthy list of relevant ontologies which may not satisfy user requirements. Users, therefore, are not equipped with expressive means to structurally and semantically describe their ontology needs. To tackle this problem, this paper
The Common Criteria (CC) provides comprehensive guidelines for the evaluation and certification of IT security. Due to the complexity of CC, CC-based certification process is quite time-consuming. The research aims to develop a CC Ontology and then construct an ontology-based tool supporting CC knowledge query, markup, review, and report functions. Results of this research can improve the understandability...
search efficiency. A prototype system has been implemented in light of this approach. Given a keyword combined query, the system outputs a ranked list of relative results according to the semantic similarity. In the experiment, the system achieved the better result than traditional keyword based search.
(UDDI) was not designed to accommodate these emerging requirements. To solve the problems of storing QoS in UDDI and aggregating QoS values, three different approaches, namely type, keyword based and ontological approaches to model QoS tModel (technical model) have been proposed. The aim is to study these approaches and
Most of the search engines search for keywords to answer the queries from users. The search engines usually search web pages for the required information. However they filter the pages from searching unnecessary pages by using advanced algorithms. These search engines can answer topic wise queries efficiently and
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
with different objectives, contexts, granularities, and educational values. This presents a wide range of options to the user. Due mainly to the amount of options available and the lack of qualification standards, it is difficult use keywords to select learning objects that will maximize the learning process in a
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.