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.
One of the challenging problem that Web service technology is now facing is effective service discovery. To solve the deficiencies of Web service description, matching and choosing under WSDL language, this paper presents a web service discovery method based on keyword clustering and concept expansion, mainly from the
How to find the teaching resources according to users' demand quickly and accurately on the Internet is urgent to be solved. This paper proposes a design of pretreatment for keyword-based search over network teaching resource database based on ontology. Firstly, the teaching ontology is created according to the
suggested in this study. Four keyword-based research networks, with journal paper or research project as network actors, constructed previously are selected as the targets of this empirical study: 1) Technology Foresight Paper Network: 181 papers and 547 keywords, 2) Regional Innovation System Paper Network: 431 papers and
The purpose of the following report is to introduce a model that makes it possible to efficiently search data by using keyword-based concept network for reliable access of information which is rapidly increasing in the mobile cloud. A keyword-based concept network is a method with the application of ontology. However
In the information retrieval process, the selection of keywords and the generation of queries are very critical for the efficient retrieval. However, users experience the difficulties of selecting major keywords without being aware of the domain context. This paper proposes an automatic query generation method using n
The traditional layout of news websites, the combination of classified hierarchical browsing, headline recommendation and keyword-based search, has been used for many years. The keyword-based search is considered to be the most powerful tool for news browsing and retrieval. Unfortunately, the keyword-based query
Due to the huge number of research articles in the biomedical domain, it becomes more and more important to develop methods to find relevant articles of our specific research interests. Keyword extraction is a useful method to find important topics from documents and summarize their major information. Unfortunately
The Holy Quran, due to its unique style and allegorical nature, needs special attention about searching and information retrieval issues. The legacy keyword searching techniques are incapable of retrieving semantically relevant verses. In this paper, we address the deficiencies of key word based searching and the
With the development of Internet, more and more on-line information has become precious wealth that we can access to. High quality information is often stored in dedicated digital libraries. However, query system of most digital libraries based on keyword matching couldnpsilat make users satisfied. This paper presents
Currently keyword search is a prominent data retrieval method for the Web because the simple and efficient nature of the keyword processing allows it to process a large amount of information with fast response. However, keyword search approaches do not formally capture the clear meaning of a keyword query and fail to
precision ratio and novelty ratio than that of web search engines. Based on case studies, we found that there are four main types of query suggestion within digital library environments, namely spelling suggestion, hot keyword suggestion, personalized suggestion and semantic suggestion. These approaches are, however, hardly to
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
Due to the explosive growth of the amount of Web information, the effectiveness of keyword-based searching methods appears to reach a limit. One major reason is that the mixture of content and presentation information hinders machines in understanding the context of Web information and as a result, the performance of
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
) Discipline Ontology is constructed, which is the formalization for concepts and the relationships between concepts existing in some discipline domain. OWL is adopted as Discipline Ontology description language; 2) Inference rules are defined on the basis of Discipline Ontology. Semantic extension on keyword from user is
Traditional information gathering systems are mostly keyword-based that are lack of semantic comprehension and analysis ability and can't guarantee the comprehensiveness and accuracy of information gathering. This paper proposes Chinese patent information gathering model based on domain ontology, which can visualize
introduction of Ranking Evaluator. Compared to previous works, another important idea we proposed is that we use a Search Arbiter to judge whether the query is answered by Keyword-based Search Engine or Ontology Search Engine, which is based on whether there is not enough ontology knowledge or not. Also, key techniques are
combine folksonomy, keyword and facet-based retrieval methods to retrieve software requirements related to users' interests. We add semantic ontology and users' feedback to obtain better software requirements that satisfy users' preferences to enhance software requirements retrieval performance. Finally, we demonstrate the
In this paper, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of
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
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.