| 000 -LEADER |
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02020nam a22002297a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
CITU |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20211007162246.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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211007b ||||| |||| 00| 0 eng d |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.35 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Preferred name for the person |
Feliscuzo, Larmie T.S. |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
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| Title |
Machine-assisted human translation for English to Tagalog and vice versa / |
| Remainder of title |
Larmie T.S. Feliscuzo. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
v, 30 pages : |
| Dimensions |
28 cm. |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
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rdamedia |
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unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
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rdacarrier |
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volume |
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nc |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (Master in Computer Science) -- Cebu Institute of Technology - University, October 2006. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Machine-Assisted Human Translation for English to Tagalog and vice versa is a tool designed to translate simple sentences to another language whose dictionary and grammatical rules are available in the database. It provides users with multiple translation of an English sentence to Tagalog sentences with statistical information on usage that would help them decide the best sentence to use during the translation process. Equivalent Tagalog sentences would have the same English translation. It would give the user the option to save a word if it encounters unknown word in the document to be interpreted. At present, it could support English to Tagalog and vice versa but it is designed to support multiple languages in the future.<br/><br/> In cases where a word could have a multiple part-of-speech, it uses a technique based from the part-of-speech tag of the previous and next word using rules derived from hand-tagged sentences. It uses Augmented Transition Network (ATN) parser in the implementation of its parser that detects the structure of a particular sentence.<br/><br/>It provides a look-up for synonyms of translated words in a sentence. It uses English as its base language and it is designed as an aid to human translators. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Natural language processing (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Translation and interpretation. |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Source of classification or shelving scheme |
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| Item type |
THESIS / DISSERTATION |