M. E. Maron and J. L. Kuhns, "On relevance, probabilistic indexing and information retrieval," Journal of the ACM, vol. 7, pp. 216--244, 1960.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....that D was the relevant document in the user s mind, given that Q was the query produced, i.e. P (D is RjQ) and rank the documents based on this measure. Using probability models for information retrieval has a history almost four decades long, beginning with the work of Maron and Kuhns [11], and first seeing real application in the standard probability model pioneered by Robertson and Sparck Jones [15] More recently,however, the introduction of ad hoc constants and non linear smoothing functions have improved performance steadily at the cost of drifting further and further from ....

M. E. Maron and K. L. Kuhns, "On relevance, probabilistic indexing and information retrieval." Journal of the Associations of Computing Machinery, 7, pp. 216-244 (1960).

.... VECTOR SPACE REPRESENTATIONS The vector space (or vector processing) model is a model for document and query representation, that includes operations for matching queries to documents based on measures of similarity [61] The vector model is an alternative to the Boolean and probabilistic models [45, 76] for information retrieval. In the vector processing model documents are represented as vectors of binary or numeric term weights. These representations are typically interpreted geometrically as coordinates in a space of index terms. Queries and user profiles [36, 38] are also represented as ....

Maron, M.E. and Kuhns, J.L. "On relevance, probabilistic indexing, and information retrieval". Journal of the ACM 7 (1960), 216-244.

....that D was the relevant document in the user s mind, given that Q was the query produced, i.e. P (D is RjQ) and rank the documents based on this measure. Using probability models for information retrieval has a history almost four decades long, beginning with the work of Maron and Kuhns [10], and first seeing real application in the standard probability model pioneered by Robertson and Sparck Jones [14] More recently, however, the introduction of ad hoc constants and non linear smoothing functions have improved performance steadily at the cost of straying further and further from ....

M. E. Maron and K. L. Kuhns, "On relevance, probabilistic indexing and information retrieval." Journal of the Associations of Computing Machinery, 7, pp. 216-244 (1960).

.... as use of indexing vocabularies, indexing indeterminacy, and users inability to completely specify information needs[41] Retrieving information that meets users information needs is an iterative process, and techniques which explicitly incorporate users judgments, such as relevance feedback[48], provide means to automate some aspects of user guided retrieval. It is also clear that mechanisms providing alternative paths of access to information can enhance retrieval effectiveness[7] One promising approach for enhancing information retrieval through the Internet is visualization to ....

Maron, M. E. and Kuhn, J. L. 1960. "On relevance, probabilistic indexing, and information retrieval ". Journal of the Association for Computing Machinery, 7(3), 216-244.

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M. E. Maron and J. L. Kuhns, "On relevance, probabilistic indexing and information retrieval," Journal of the ACM, vol. 7, pp. 216--244, 1960.

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