Long Short-Term Memory Based Query Auto-Completion

Qureshi A. R. A., AKCAYOL M. A.

8th International Conference on Electrical and Electronics Engineering, ICEEE 2021, Antalya, Türkiye, 9 - 11 Nisan 2021, ss.259-266 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/iceee52452.2021.9415918
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.259-266
  • Anahtar Kelimeler: query auto-completion, long short-term memory, one-hot encoding, textual information retrieval
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2021 IEEE.In this study, Long Short-Term Memory (LSTM) based Query Auto-Completion (QAC) has been proposed to generate a query completion list using input prefix. The performance of the QAC system has been evaluated by using the relevancy score, and the quality of the QAC generation system has been evaluated by using partial and complete matching strategies, success rate, normalized discounted cumulative gain, and mean average precision. The proposed LSTM based QAC system has been extensively tested using AOL and ORCAS datasets. According to experimental results, the performance of the proposed QAC system is more successful with the partial matching strategy. Also, the quality of the QAC generation list by the proposed QAC system is better on the complete matching strategy.