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Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types ...
The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model .
An evaluation is a systematic and objective examination concerning the relevance, effectiveness, efficiency, impact and sustainabilities of activities in the light of specified objectives. [2] The idea in evaluating projects is to isolate errors in order to avoid repeating them and to underline and promote the successful mechanisms for current ...
Once relevance levels have been assigned to the retrieved results, information retrieval performance measures can be used to assess the quality of a retrieval system's output. In contrast to this focus solely on topical relevance, the information science community has emphasized user studies that consider user relevance. [3]
A business plan is a formal written document containing the goals of a business, the methods for attaining those goals, ...
S.M.A.R.T. (or SMART) is an acronym used as a mnemonic device to establish criteria for effective goal-setting and objective development. This framework is commonly applied in various fields, including project management, employee performance management, and personal development.
Organizations may also plan their financial statements (i.e., balance sheets, income statements, and cash flows) for several years when developing their strategic plan, as part of the goal-setting activity. The term operational budget is often used to describe the expected financial performance of an organization for the upcoming year. Capital ...
Pseudo-relevance feedback is efficient in average but can damage results for some queries, [7] especially difficult ones since the top retrieved documents are probably non-relevant. Pseudo-relevant documents are used to find expansion candidate terms that co-occur with many query terms. [ 8 ]
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