Items related to Optimal Best-Match Retrieval (Classic Reprint)
Synopsis
Excerpt from Optimal Best-Match Retrieval
The best-match problem (also known as the post office problem or the nearest neighbor problem arises in many applications, such as database management information retrieval [4, 7, molecular biology [15, pattern classification [11, 14, 18] and computational geometry The problem is to find, among a file of objects, the ones which are most similar or closest to a given target according to some similarity distance measure. To answer this type of queries, one could compute the distance between each object of the file and the target, and then search for the objects with minimum distance. The major problem with this approach is its computational expense, particularly when there are many targets to be identified and the file is large. To reduce computational effort, many techniques have been presented in the literature.
About the Publisher
Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
"synopsis" may belong to another edition of this title.
Search results for Optimal Best-Match Retrieval (Classic Reprint)
Stock Image
Optimal Best-Match Retrieval (Classic Reprint)
Print on DemandSeller: Forgotten Books, London, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. Print on Demand. This book provides a new scheme to answer best-match queries from a database containing a collection of objects. Best-match queries consist of identifying the closest (according to some similarity measure) objects to a given target. The author's technique generalises earlier approaches and allows for any kind of topology in data structures, which means permitting an arbitrary set of object pairs in the database with absent distances. A Floyd-Warshall style algorithm is used to achieve the optimal approximation of those unknown distances. The proposed heuristic for choosing objects to compare against the target outperforms those suggested in previous work. Artificial data and actual protein sequences are used to illustrate the scheme, demonstrating some weaknesses and advantages of the technique, and showing the superior performance of the author's scheme over others when given the same data structure. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781334254406_0
Quantity: Over 20 available
Stock Image
Optimal BestMatch Retrieval Classic Reprint
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LX-9781334254406
Quantity: 15 available
Stock Image
Optimal BestMatch Retrieval Classic Reprint
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LX-9781334254406
Quantity: 15 available
Seller Image
OPTIMAL BEST-MATCH RETRIEVAL (
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. KlappentextrnrnExcerpt from Optimal Best-Match RetrievalThe best-match problem (also known as the post office problem or the nearest neighbor problem [11] arises in many applications, such as database management information retrieval [4,. Seller Inventory # 2148126788
Quantity: Over 20 available