Using Self-Organizing Map and data mining measurements to improve Thai-English statistical machine translation

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Wongdeethai S., Polvichai J., Netjinda N.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2011

ISBN: 9781424492244

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960282277&doi=10.1109%2fICISA.2011.5772395&partnerID=40&md5=6b21e79bbd6c3c9b89ff74c18a7e3d7e

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

The objective of this work is improving for Statistical Machine (SMT) by using Self - Organizing MAP (SOM). In general we have 2 processes for Training and Translating. Training process is use for preparing resource from a number of bilingual corpuses, which are used for translating process. But, we still have a lot of irrelevant resource of data. Major method for this research is highlighted on new SOM Method for filtering on irrelevant data off from final translation model as much as possible. The initial result identify that using SOM for filtering process is able to filtering out incorrect pairing more efficient than general statistical method. Hence, the better statistical translation model can be created. In assumption, the efficiency of Thai-English SMT could be improved from using this improve statistical model. ฉ 2011 IEEE.

คำสำคัญ

Self-Organizing Map, Statistical Machine Translation