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A common approach to performing keyword search over relational databases is to find the minimum Steiner trees in database graphs. These methods, however, are rather expensive as the minimum Steiner tree problem is known to be NP-hard. Further, these methods cannot benefit from DBMS capabilities. We propose a new
This paper describes a conceptual structure of application, which based on user preferences personalize news feeds. Personalize news feeds application allows for user to save time and gives him only interesting articles, news.
and departmental Information content, activities, projects, services, tools, knowledge, events, etc. It allows users to select among three search options that are; keyword-based search, location-based search, and user profile-based search. The novel approach described in this paper combines users mobility, including
special data record and new record model on fuzzy set are given. By calculating the membership of keyword, new fuzzy closeness functions are proposed to classify the information. Finally, examples prove that this algorithm can effectively and automatically classify input information of database, the accuracy and intelligence
introduce essential technologies enabling to inspect documents securely and to change specific keywords to normal words, in case that a higher security level document should be converted to a lower security level document.
subcontract documents. This sub-item contract template have been established through the help of legal advisers from Construction Association to review these documentation. Database is applied to store frequently used variables. When parser reads these keywords, the values stored in database are fetched and inserted into output
to create a new entry in a database from the Neurology Laboratory measurements. The advantage of the web application is to view patient's saved records, filter entries with by keywords, show a preview of a curve and download electro physical data in three different formats (edf, dat, xml). The output of the proposed
is to stem and eliminate common words. The aim of this research is to stem words from Persian documents to make their use more efficient in text summarization, the present method is to eliminate words and stem keywords. The compound of existing techniques in the words network was used to create a Persian database using
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.