This work aims to design and develop a system for fast searching of variable length of strings taking the advantage of using the enumeration and multilevel hashing to improve the searching time by providing a semi-uniform searching performance, with the use of weighting scheme and some data structure concepts. The designed system takes into consideration various kinds of factors that affect the searching process (e.g. the search space size). Also, in order to provide an efficient system performance capable of handling some spelling mistakes an updated algorithm for string similarity measure was proposed, which is a combined set of well-known algorithms with some improvements by using certain conditions which are introduced after conducting on a number of experimental tests. The proposed algorithm “Optimized Dice Coefficient, N-grame and Damerau-Levenshtein Algorithms using Numeration Operations (ODADNN)” provides efficient results to assess the similarity between two words without the need to restrict the words length.
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Safa S.Abdul-Jabbar received her bachelor degree in the field of computer science from University of Baghdad/College of Science for Women, in 2009.Then,she is working as a lecturer at the Computer Science Department/College of Science for Women/University of Baghdad up till now. In 2017 she is received her master’s degree from University of Baghdad
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work aims to design and develop a system for fast searching of variable length of strings taking the advantage of using the enumeration and multilevel hashing to improve the searching time by providing a semi-uniform searching performance, with the use of weighting scheme and some data structure concepts. The designed system takes into consideration various kinds of factors that affect the searching process (e.g. the search space size). Also, in order to provide an efficient system performance capable of handling some spelling mistakes an updated algorithm for string similarity measure was proposed, which is a combined set of well-known algorithms with some improvements by using certain conditions which are introduced after conducting on a number of experimental tests. The proposed algorithm 'Optimized Dice Coefficient, N-grame and Damerau-Levenshtein Algorithms using Numeration Operations (ODADNN)' provides efficient results to assess the similarity between two words without the need to restrict the words length. 156 pp. Englisch. Seller Inventory # 9786202050142
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Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: S. Abdul-Jabbar SafaSafa S.Abdul-Jabbar received her bachelor degree in the field of computer science from University of Baghdad/College of Science for Women, in 2009.Then,she is working as a lecturer at the Computer Science Departme. Seller Inventory # 175567330
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work aims to design and develop a system for fast searching of variable length of strings taking the advantage of using the enumeration and multilevel hashing to improve the searching time by providing a semi-uniform searching performance, with the use of weighting scheme and some data structure concepts. The designed system takes into consideration various kinds of factors that affect the searching process (e.g. the search space size). Also, in order to provide an efficient system performance capable of handling some spelling mistakes an updated algorithm for string similarity measure was proposed, which is a combined set of well-known algorithms with some improvements by using certain conditions which are introduced after conducting on a number of experimental tests. The proposed algorithm 'Optimized Dice Coefficient, N-grame and Damerau-Levenshtein Algorithms using Numeration Operations (ODADNN)' provides efficient results to assess the similarity between two words without the need to restrict the words length.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch. Seller Inventory # 9786202050142
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Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Fast String Searching Based on Multilevel Hashing | Building Word Dictionary for Fast String Search | Safa S. Abdul-Jabbar (u. a.) | Taschenbuch | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202050142 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 113378877
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Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work aims to design and develop a system for fast searching of variable length of strings taking the advantage of using the enumeration and multilevel hashing to improve the searching time by providing a semi-uniform searching performance, with the use of weighting scheme and some data structure concepts. The designed system takes into consideration various kinds of factors that affect the searching process (e.g. the search space size). Also, in order to provide an efficient system performance capable of handling some spelling mistakes an updated algorithm for string similarity measure was proposed, which is a combined set of well-known algorithms with some improvements by using certain conditions which are introduced after conducting on a number of experimental tests. The proposed algorithm 'Optimized Dice Coefficient, N-grame and Damerau-Levenshtein Algorithms using Numeration Operations (ODADNN)' provides efficient results to assess the similarity between two words without the need to restrict the words length. Seller Inventory # 9786202050142
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Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 156 pages. 8.66x5.91x0.36 inches. In Stock. Seller Inventory # zk6202050144
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