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, keywords are extracted from each advertisement, and the most correlated keywords to each category are identified through Term Frequency and Inverted Domain Frequency (TF-IDF) analysis. Thus, the ontology of the advertisement world is built. Normalized Google Distance (NGD) values between keywords are computed to derive the
In most cases, users are unable to precisely translate their information needs into a query format for the search system to process. Users often submit queries containing terms or keywords that do not match with their intended information. That is why user normally reformulates queries several times to gain more
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
employed in query reformulation process. This work proposes the use of crop characteristic category element in reformulating query, as well as combination with ontology and query keyword elements. The experimental results show that the use of crop characteristic category in reformulating query has significantly improved the
Service discovery is a mechanism for finding services, the existing service discovery mechanisms offer low retrieval precision and recall. The current problem with service inventories such as UDDI is the retrieval process which associated with the search engines that support only syntactic, keyword-Oriented search
understanding of domain in which semantics of data is machine understandable. Second, we make in Raspberry Pi an interface which has the capability to recognize speech queries and give an oral response. Our interface analyzes each speech query, convert speech to text and extract keywords from the text. Later, these keywords are
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
This paper introduces an application developed with FAO Agrovoc ontology and Google AJAX API. FAO Agrovoc ontology is not only an agricultural concepts collection but also the relationships among the concepts, Google API can be used to submit keywords to Google search engine and get the retrieval results from Google
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.