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, the same is true for the semantic information about these entities that can be fetched from the available LOD (i.e. their properties and associations with other entities). To this end, in this paper we propose a Link Analysis-based method which is used for (a) ranking (and thus selecting to show) the more important
The goal of information retrieval (IR) is to identify documents which best satisfy users' information need. The task of formulating an effective query becomes much more difficult when the target is the Web. Proposals on query refinement in IR, such as relevant feedback which needs to analyse the whole document
Given a set of keywords, we find a maximum Web query (containing the most keywords possible) that respects user-defined bounds on the number of returned hits. We assume a real-world setting where the user is not given direct access to a Web search engine's index, i.e., querying is possible only through an interface
user to get specific information related to the submitted keyword. For this reason a new criterion is used in which feedback sessions are first generated from user clicked through logs. Using Feedback session a pseudo documents are generated by calculating TF-IDF (Term Frequency Inverse Data Frequency) vectors for each
various symbols like * or! .The primary goal in designing this is to restrict ourselves by just mentioning the keyword using the truncation or wildcard symbols rather than expanding the keyword into sentential form. Second part consists of the review on subdivision based on wildcards. It is based on the observation that
FCA, a session interest concept is defined as a pair of extent and intent where the extent covers a set of documents selected by the user among the search results and the intent covers a set of keyword features extracted from the selected documents. And, in order to make a concept network grow, we need to calculate the
improving user's goals and needs. The content based ranking is based on contents and keywords rather than link structure and keywords provided by search engines. Search engines results are retrieved based on the user query. Also, usage based ranking algorithm consider the past user navigation pattern and analyze the behavior
Information retrieval and web search present a Challenging Question to researches. Today users urge for accurate and precise hands on information from Search Machine. Interpreting of user query goal is major challenge in past and present. Numerous algorithms and Frameworks have be proposed, but fail to incorporate
framework, selected keywords, composed the keywords into composite index, found a strong correlation, and finally a result of prediction sales was given in the end of the paper.
Nowadays, Internet users are familiar with the Web searching process; and searching is the most common task performed on the Web. However, the web search is especially difficult for beginners when they try to utilize a keyword query language. Subsequently, beginners usually try to find information with ambiguous
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