Building Language Resources for Intent Analysis of Travel-Recommendation Chatbots

doi:10.18627/jslg.39.3.202311.243

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2023 Vol.39, Issue 3 Next Page

Research Article

Building Language Resources for Intent Analysis of Travel-Recommendation Chatbots 여행 도메인 추천봇의 요청문 의도 분석을 위한 언어자원 구축: 김신우¹, 남지순^1*
Kim, Shin-Woo¹, Nam, Jeesun^1*; ¹한국외국어대학교

¹Hankuk University of Foreign Studies

30 November 2023. pp. 243-262

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Abstract

This study proposes a methodology for efficiently generating high-quality training data required to build an intent analysis model for recommendation requests in travel domain chatbots. We investigate the correlation between reviews and recommendation requests within the travel domain to achieve this. We extracted from the reviews the three elements ({Evaluation Target, Evaluation Aspect, Evaluation Value}), and described the {Evaluation Request} element that represents query-related language patterns. We trained the intent analysis model to investigate the performance of the training data generated by the proposed methodology. We obtained F1 scores of 0.897 and 0.957 in the accommodation and restaurant domain respectively, which underlines the effectiveness of the proposed methodology.

Keywords

intent quadruple

request query analysis

local grammar graph

language data propagation

recommendation chatbot

References

고대영. 2014. 화행과 요청. 배달말, 55, 1-23. 10.1365/s35141-014-0794-7
김강희. 2020. 한국어 지시화행의 체계에 대한 소고. 국어국문학, 191, 5-40. 10.31889/kll.2020.06.191.5
김신우, 최수원, 김리아, 남지순. 2022. 후기기반 맛집 추천 챗봇 LIFU 구현을 위한 언어자원 연구. 한국외국어대학교 디코라연구센터, DICORA-TR-2022-03, 45.
남지순. 2021a. 자질기반 감성분석(FbSA) 모델의 인공지능 학습을 위한 지식베이스-패턴문법 기반 반자동 학습데이터 증강(SSP) 방법 및 장치. 한국외국어대학교 디코라연구센터, DICORA-TR-2021-10, 35.
남지순. 2021b. 이커머스 후기글 평가분석에 기반한 상품 검색 추천 챗봇 개발을 위한 학습데이터 증강 방법 및 장치. 한국외국어대학교 디코라연구센터, DICORA-TR-2021-11, 35.
민동희, 이우범. 2019. 통계적 단어 대조를 이용한 음식점 추천 챗봇 애플리케이션 구현. 융합신호처리학회 논문지, 20.1, 31-36.
소진수, 신판섭. 2020. 음식점 리뷰 감성분석을 통한 세부 평가항목별 평점 예측. 한국컴퓨터정보학회논문지, 25.6, 81-89.
유광훈, 남지순. 2017. DECO 감성사전과 LGG 문법에 기반한 관광 숙박 온라인 후기글의 감성 분석 연구. 한국사전학, 30, 100-154.
윤정우, 이윤우, 남지순. 2022. 후기기반 숙소추천 챗봇 LIST 구현을 위한 언어자원 연구. 한국외국어대학교 디코라연구센터, DICORA-TR-2022-04, 52.
윤정호, 김선호, 박규태, 박두순. 2012. 스마트폰에서 데이터마이닝을 이용한 음식추천 시스템. 한국정보처리학회 학술대회논문집, 19.1, 1379-1381.
최수원, 남지순. 2021. 이커머스 후기글 평가분석 트리플에 기반한 평가주석 데이터셋 EVAD 구축 방법론. 언어과학연구, 99, 245-272. 10.21296/jls.2021.12.99.245
한승규, 임희석. 2021. 발화 의도 예측 및 슬롯 채우기 복합 처리를 위한 한국어 데이터셋 개발. 한국융합학회논문지, 12.1, 57-63.
황창회, 남지순. 2021. 생성용 LGG에 기반한 챗봇 데이터의 RASA 호환형 데이터 컨버터 DECO-DACO. 한국외국어대학교 디코라연구센터, DICORA-TR-2021-13, 339.
Akhtar, N., Zubair, N., Kumar, A., and Ahmad, T. 2017. Aspect based Sentiment Oriented Summarization of Hotel Reviews. Procedia Comput. Sci. 115. 10.1016/j.procs.2017.09.115
Choi, S. W., Hwang, C. H., Yoo, G. H., and Nam, J. S. 2021. Construction of Evaluation-Annotated Datasets for EA-based Clothing Recommendation Chatbots. In Annual Conference on Human and Language Technology, 467-472.
Contractor, D., Patra, B., Mausam, and Singla, P. 2021. Constrained BERT BiLSTM CRF for understanding multi-sentence entity-seeking questions. Natural Language Engineering 27.1, 65-87. 10.1017/S1351324920000017
Gao, Y., Yu, W., Chao, P., Zhang, R., Zhou, A., and Yang, X. 2015. A restaurant recommendation system by analyzing ratings and aspects in reviews. In International Conference on Database Systems for Advanced Applications, Cham: Springer, 526-530. 10.1007/978-3-319-18123-3_33
Gross, M. 1997. The construction of local grammars. In E. Roche and Y. Schabès (eds.), Finite-state language processing. The MIT Press, 329-354.
Gunawan, D., Putri, F., and Meidia, H. 2020. Bershca: Bringing chatbot into hotel industry in Indonesia. Telkomnika, 18.2, 839-845. 10.12928/telkomnika.v18i2.14841
Kim, Y. and Heo, G. E. 2021. Sentiment Analysis and Network Analysis based on Review Text. Journal of the Korean Society for Library and Information Science, 55.3, 397-417.
Liu, B. 2012. Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5.1, 1-167. 10.2200/S00416ED1V01Y201204HLT016
Maynez, J., Narayan, S., Bohnet, B., and McDonald, R. 2020. On faithfulness and factuality in abstractive summarization. arXiv preprint arXiv:2005.00661. 10.18653/v1/2020.acl-main.173
Park, M. H., Park, H. S., and Cho, S. B. 2008. Restaurant recommendation for group of people in mobile environments using probabilistic multi-criteria decision making. In Asia-pacific conference on computer human interaction, 114-122. 10.1007/978-3-540-70585-7_13
Paumier, S. 2003. De la reconnaissance de formes linguistiques a l’analyse syntaxique. Ph. D. dissertation, Univ of PEMLV in France.
Ray, B., Garain, A., and Sarkar, R. 2021. An ensemble-based hotel recommender system using sentiment analysis and aspect categorization of hotel reviews. Applied soft computing, 98. 10.1016/j.asoc.2020.106935
Roh, Y., Heo, G., and Whang, S. E. 2019. A survey on data collection for machine learning: a big data-ai integration perspective. IEEE Transactions on Knowledge and Data Engineering, 33.4, 1328-1347. 10.1109/TKDE.2019.2946162
Samuel, D., Kutuzov, A., Øvrelid, L., and Velldal, E. 2023. Trained on 100 million words and still in shape: BERT meets British National Corpus. arXiv preprint arXiv:2303.09859. 10.18653/v1/2023.findings-eacl.146
Sun, L., Guo, J., and Zhu, Y. 2019. Applying uncertainty theory into the restaurant recommender system based on sentiment analysis of online Chinese reviews. World Wide Web, 22.1, 83-100. 10.1007/s11280-018-0533-x
Tran, T., Ba, H., and Huynh, V. N. 2019. Measuring hotel review sentiment: An aspect-based sentiment analysis approach. In International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, Cham: Springer, 393-405. 10.1007/978-3-030-14815-7_33
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bahlykov, N., Batra, S., Bhargava, P., Bhosale, S., Bikel, D., Blecher, L., Ferrer, C. C., Chen, M., Cucurull, G., Esiobu, D., Fernandes, J., Fu, J., Fu, W., Fuller, B., Gao, C., Goswami, V., Goyal, N., Hartshorn, A., Hosseini, S., Hou, R., Inan, H., Kardas, M., Kerkez, V., Khabsa, M., Kloumann, I., Korenev, A., Koura, S. P., Lachaux, M., Lavril, T., Lee, J., Liskovich, D., Lu, Y., Mao, Y., Martinet, X., Mihaylov, T., Mishra, P., Molybog, I., Nie, Y., Pulton, A., Reizenstein, J., Rungta, R., Saladi, K., Schelten, A., Silva, R., Smith, M. E., Subramanian, R., Tan, E. X., Tang, B., Taylor, R., Williams, A., Kuan, X. J., Xu, P., Yan, Z., Zarov, I., Zhang, Y., Fan, A., Kambadur, M., Narang, S., Rodriguez, A., Stojnic, R., Edunov, S., and Scialom, T. 2023. Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288.
Yoon, J. H., Kim, S. H., Park, K. T., and Park, D. S. 2012. Food Recommendation System using Data Mining in Smartphone. In Proceedings of the Korea Information Processing Society Conference. Korea Information Processing Society, 1379-1381.

Information

Publisher :The Modern Linguistic Society of Korea
Publisher(Ko) :한국현대언어학회
Journal Title :The Journal of Studies in Language
Journal Title(Ko) :언어연구
Volume : 39
No :3
Pages :243-262
DOI :https://doi.org/10.18627/jslg.39.3.202311.243

[1] 고대영. 2014. 화행과 요청. 배달말, 55, 1-23. 10.1365/s35141-014-0794-7

[2] 김강희. 2020. 한국어 지시화행의 체계에 대한 소고. 국어국문학, 191, 5-40. 10.31889/kll.2020.06.191.5

[3] 김신우, 최수원, 김리아, 남지순. 2022. 후기기반 맛집 추천 챗봇 LIFU 구현을 위한 언어자원 연구. 한국외국어대학교 디코라연구센터, DICORA-TR-2022-03, 45.

[4] 남지순. 2021a. 자질기반 감성분석(FbSA) 모델의 인공지능 학습을 위한 지식베이스-패턴문법 기반 반자동 학습데이터 증강(SSP) 방법 및 장치. 한국외국어대학교 디코라연구센터, DICORA-TR-2021-10, 35.

[5] 남지순. 2021b. 이커머스 후기글 평가분석에 기반한 상품 검색 추천 챗봇 개발을 위한 학습데이터 증강 방법 및 장치. 한국외국어대학교 디코라연구센터, DICORA-TR-2021-11, 35.

[6] 민동희, 이우범. 2019. 통계적 단어 대조를 이용한 음식점 추천 챗봇 애플리케이션 구현. 융합신호처리학회 논문지, 20.1, 31-36.

[7] 소진수, 신판섭. 2020. 음식점 리뷰 감성분석을 통한 세부 평가항목별 평점 예측. 한국컴퓨터정보학회논문지, 25.6, 81-89.

[8] 유광훈, 남지순. 2017. DECO 감성사전과 LGG 문법에 기반한 관광 숙박 온라인 후기글의 감성 분석 연구. 한국사전학, 30, 100-154.

[9] 윤정우, 이윤우, 남지순. 2022. 후기기반 숙소추천 챗봇 LIST 구현을 위한 언어자원 연구. 한국외국어대학교 디코라연구센터, DICORA-TR-2022-04, 52.

[10] 윤정호, 김선호, 박규태, 박두순. 2012. 스마트폰에서 데이터마이닝을 이용한 음식추천 시스템. 한국정보처리학회 학술대회논문집, 19.1, 1379-1381.

[11] 최수원, 남지순. 2021. 이커머스 후기글 평가분석 트리플에 기반한 평가주석 데이터셋 EVAD 구축 방법론. 언어과학연구, 99, 245-272. 10.21296/jls.2021.12.99.245

[12] 한승규, 임희석. 2021. 발화 의도 예측 및 슬롯 채우기 복합 처리를 위한 한국어 데이터셋 개발. 한국융합학회논문지, 12.1, 57-63.

[13] 황창회, 남지순. 2021. 생성용 LGG에 기반한 챗봇 데이터의 RASA 호환형 데이터 컨버터 DECO-DACO. 한국외국어대학교 디코라연구센터, DICORA-TR-2021-13, 339.

[14] Akhtar, N., Zubair, N., Kumar, A., and Ahmad, T. 2017. Aspect based Sentiment Oriented Summarization of Hotel Reviews. Procedia Comput. Sci. 115. 10.1016/j.procs.2017.09.115

[15] Choi, S. W., Hwang, C. H., Yoo, G. H., and Nam, J. S. 2021. Construction of Evaluation-Annotated Datasets for EA-based Clothing Recommendation Chatbots. In Annual Conference on Human and Language Technology, 467-472.

[16] Contractor, D., Patra, B., Mausam, and Singla, P. 2021. Constrained BERT BiLSTM CRF for understanding multi-sentence entity-seeking questions. Natural Language Engineering 27.1, 65-87. 10.1017/S1351324920000017

[17] Gao, Y., Yu, W., Chao, P., Zhang, R., Zhou, A., and Yang, X. 2015. A restaurant recommendation system by analyzing ratings and aspects in reviews. In International Conference on Database Systems for Advanced Applications, Cham: Springer, 526-530. 10.1007/978-3-319-18123-3_33

[18] Gross, M. 1997. The construction of local grammars. In E. Roche and Y. Schabès (eds.), Finite-state language processing. The MIT Press, 329-354.

[19] Gunawan, D., Putri, F., and Meidia, H. 2020. Bershca: Bringing chatbot into hotel industry in Indonesia. Telkomnika, 18.2, 839-845. 10.12928/telkomnika.v18i2.14841

[20] Kim, Y. and Heo, G. E. 2021. Sentiment Analysis and Network Analysis based on Review Text. Journal of the Korean Society for Library and Information Science, 55.3, 397-417.

[21] Liu, B. 2012. Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5.1, 1-167. 10.2200/S00416ED1V01Y201204HLT016

[22] Maynez, J., Narayan, S., Bohnet, B., and McDonald, R. 2020. On faithfulness and factuality in abstractive summarization. arXiv preprint arXiv:2005.00661. 10.18653/v1/2020.acl-main.173

[23] Park, M. H., Park, H. S., and Cho, S. B. 2008. Restaurant recommendation for group of people in mobile environments using probabilistic multi-criteria decision making. In Asia-pacific conference on computer human interaction, 114-122. 10.1007/978-3-540-70585-7_13

[24] Paumier, S. 2003. De la reconnaissance de formes linguistiques a l’analyse syntaxique. Ph. D. dissertation, Univ of PEMLV in France.

[25] Ray, B., Garain, A., and Sarkar, R. 2021. An ensemble-based hotel recommender system using sentiment analysis and aspect categorization of hotel reviews. Applied soft computing, 98. 10.1016/j.asoc.2020.106935

[26] Roh, Y., Heo, G., and Whang, S. E. 2019. A survey on data collection for machine learning: a big data-ai integration perspective. IEEE Transactions on Knowledge and Data Engineering, 33.4, 1328-1347. 10.1109/TKDE.2019.2946162

[27] Samuel, D., Kutuzov, A., Øvrelid, L., and Velldal, E. 2023. Trained on 100 million words and still in shape: BERT meets British National Corpus. arXiv preprint arXiv:2303.09859. 10.18653/v1/2023.findings-eacl.146

[28] Sun, L., Guo, J., and Zhu, Y. 2019. Applying uncertainty theory into the restaurant recommender system based on sentiment analysis of online Chinese reviews. World Wide Web, 22.1, 83-100. 10.1007/s11280-018-0533-x

[29] Tran, T., Ba, H., and Huynh, V. N. 2019. Measuring hotel review sentiment: An aspect-based sentiment analysis approach. In International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, Cham: Springer, 393-405. 10.1007/978-3-030-14815-7_33

[30] Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bahlykov, N., Batra, S., Bhargava, P., Bhosale, S., Bikel, D., Blecher, L., Ferrer, C. C., Chen, M., Cucurull, G., Esiobu, D., Fernandes, J., Fu, J., Fu, W., Fuller, B., Gao, C., Goswami, V., Goyal, N., Hartshorn, A., Hosseini, S., Hou, R., Inan, H., Kardas, M., Kerkez, V., Khabsa, M., Kloumann, I., Korenev, A., Koura, S. P., Lachaux, M., Lavril, T., Lee, J., Liskovich, D., Lu, Y., Mao, Y., Martinet, X., Mihaylov, T., Mishra, P., Molybog, I., Nie, Y., Pulton, A., Reizenstein, J., Rungta, R., Saladi, K., Schelten, A., Silva, R., Smith, M. E., Subramanian, R., Tan, E. X., Tang, B., Taylor, R., Williams, A., Kuan, X. J., Xu, P., Yan, Z., Zarov, I., Zhang, Y., Fan, A., Kambadur, M., Narang, S., Rodriguez, A., Stojnic, R., Edunov, S., and Scialom, T. 2023. Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288.

[31] Yoon, J. H., Kim, S. H., Park, K. T., and Park, D. S. 2012. Food Recommendation System using Data Mining in Smartphone. In Proceedings of the Korea Information Processing Society Conference. Korea Information Processing Society, 1379-1381.

The Journal of Studies in Language ISSN:1225-4770(Print) 2671-6151(Online) 언어연구

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