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04500nam a2200289Ia 4500 |
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76550 |
| 003 - CONTROL NUMBER IDENTIFIER |
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FT6176 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20251106173115.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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190220n 000 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Description conventions |
rda |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA76.9 C33 2010 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
. |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Cadag, Eu Rey T. and De Leon, Ann Clariz T. |
| 245 #0 - TITLE STATEMENT |
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| Title |
Enhancement of N-Gram Algorithm for an accurate and precise prediction |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2010 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Other physical details |
Undergraduate Thesis: (BSCS major in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2010. |
| 336 ## - CONTENT TYPE |
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. |
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text |
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rdacontent |
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0 |
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unmediated |
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rdamedia |
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volume |
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rdacarrier |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
ABSTRACT: Word Prediction aims at easing word insertion in textual software by guessing the next word, or by giving the user list of possible options for the next word. The main purpose of word prediction is to speed up typing, but it can also help dyslexic people reducing writing error. Several problems were found in the N-Gram Algorithm for Word Prediction but the three major problems that was answered by the proponents are the following: 1. The existing algorithm does not consider the presence of special symbols when used in a word. When the user types words having the special symbols such as hyphen and aposthrophe, the algorithm us incapable of predicting and therefore could not add the new word in alist. 2. There are some English words that are not seen in the dictionary because they include suffixes but are still valid. Example approximation, prediction, consideration. Those words that are seldom used are not predicted by the algorithm because it only predicts words which have more frequency of usage. 3. When words having the same frequency of usage are used for prediction, the algorithm only selects the word that was previously typed by the user. The proponents of the study were able to meet the following objectives. 1. To recognize the predict a word that has special symbols and adds it to list of optins for prediction. 2. To have an access to the least used words and used it. 3. To use and choose the precise and specific word for the user. This will help the users, particularly the Encoder, Researchers and Disorder people, to further increase and maximise the value of their working hours. The study is mainly focused on the prediction of words based on the N-gram Algorithm, that it will be used the users more productivity. This will not develop another algorithm category, but just an enhancement of it. Word prediction or word completion have not been found to increase typing speed when using a standard keyboard or other methods of input that do not require the individual to look away from the source document. This study differed from earlier work by combining word prediction and word completion with input methods that included the need to look away from a source document, so that this factor would be constant. This study demonstrated that these features could increase typing speed for individuals using such input methods but that the cognitive load of the tools continues to distract users. In spite of the improved typing speeds achieved, many of the individuals in this study considered word prediction and word completion to be “frustration may stem from the cognitive demands of scanning the word list, or from the interruption in the flow of ideas when using a word prediction. Further research should whether the frustration of using a word prediction program can be limited by different means of list presentation or through experience with the input method. The enhanced version of Word Prediction preserves its word and shorthand prediction features, and at the same time, has an improved storage of words through integrating the software with a textile where all the words, terms and short hands will be archived. In order to achieve the purpose of explaining the function of Word Prediction, the thesis will be use Microsoft Visual C++ to demonstrate. Completing the study according to its objectives is not the main goal of this thesis, but to make Word Prediction more productive and functional as a word prediction software. But due to time constraints, imperfections and other problems still exist in the software. And with that cause, it is therefore recommended to study the enhanced software for further modifications. |
| 506 ## - RESTRICTIONS ON ACCESS NOTE |
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5 |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE |
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| Terms governing use and reproduction |
5 |
| 655 ## - INDEX TERM--GENRE/FORM |
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academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Institution code [OBSOLETE] |
lcc |
| Item type |
Thesis/Dissertation |
| Source of classification or shelving scheme |
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