Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(answering time). Showing records 1 – 2 of 2 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Hong Kong University of Science and Technology

1. Zhong, Tao CSE. Multi-task learning for question answering.

Degree: 2017, Hong Kong University of Science and Technology

Nowadays, chatbots, or dialogue systems, become quite popular and lots of companies invest large amounts of money on them. Chatbots can be divided into two categories, namely open-domain bots and task-oriented bots. The big challenge in open-domain chatbots is that the domain is not limited. As for task-oriented chatbots, they focus on a particular domain such as booking flight tickets, etc. Question answering (QA) in dialogue can be treated as a single-turn conversation. Two approaches are applied to produce answers, namely, retrieval-based approach and generation-based approach. Retrieval-based question answering(QA) aims to select an appropriate answer from a predefined repository of QA according to a user’s question. Pervious research usually employs one kind of discriminative model such as dual encoder based neural network to improve the performance of QA classification, commonly resulting in overfitting. To deal with the problem, we investigate multi-task learning(MTL) as a regularization for retrieval-based QA, jointly training main task and auxiliary tasks with shared representations for exploiting commonalities and differences. Our main task is a QA classification. And we design two auxiliary tasks in MTL: 1) learning sequence mapping of actual QA pairs via sequence to sequence learning and 2) RNN language model without relying on labeled data. Experimental results on Ubuntu Dialogue Corpus demonstrate the superiorities of our proposed MTL method over baseline systems. Generation-based question answering (QA), which usually based on seq2seq model, generates answers from scratch. One problem with seq2seq model is that it will generate high-frequency and generic answers, due to maximizing log-likelihood objective function. We investigate multi-task learning paradigm which takes seq2seq model as the main task and the binary QA classification as the auxiliary task. The main task and the auxiliary task are learned jointly, improving generalization and making full use of classification labels as extra evidence to guide the answer generalization. Experimental results on both automatic evaluations and human annotations demonstrate the superiorities of our proposed MTL method over baselines.

Subjects/Keywords: Question-answering systems ; Intelligent agents (Computer software) ; Real-time data processing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhong, T. C. (2017). Multi-task learning for question answering. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-91092 ; https://doi.org/10.14711/thesis-991012554769203412 ; http://repository.ust.hk/ir/bitstream/1783.1-91092/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhong, Tao CSE. “Multi-task learning for question answering.” 2017. Thesis, Hong Kong University of Science and Technology. Accessed January 19, 2020. http://repository.ust.hk/ir/Record/1783.1-91092 ; https://doi.org/10.14711/thesis-991012554769203412 ; http://repository.ust.hk/ir/bitstream/1783.1-91092/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhong, Tao CSE. “Multi-task learning for question answering.” 2017. Web. 19 Jan 2020.

Vancouver:

Zhong TC. Multi-task learning for question answering. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2017. [cited 2020 Jan 19]. Available from: http://repository.ust.hk/ir/Record/1783.1-91092 ; https://doi.org/10.14711/thesis-991012554769203412 ; http://repository.ust.hk/ir/bitstream/1783.1-91092/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhong TC. Multi-task learning for question answering. [Thesis]. Hong Kong University of Science and Technology; 2017. Available from: http://repository.ust.hk/ir/Record/1783.1-91092 ; https://doi.org/10.14711/thesis-991012554769203412 ; http://repository.ust.hk/ir/bitstream/1783.1-91092/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

2. Chiang, Meng-yuan. The impact on answering time, response rate and user experience of using color on web survey.

Degree: Master, Information Management, 2017, NSYSU

Web survey has been widely used for academic research, market survey, etc. Therefore, how to improve the efficiency and performance on questionnaires becomes an important issue. This research is to find out how it impacts the answering time, response rate, and user experience when we add colors on the survey page. To examine the effect of color, two experiments of online survey had been conducted, the first experiment added the color on the option of the questions, and the second one added color on the keyword and the options of the questions. These surveys had recorded the answering time and response rate of the subject, and the user experience by user experience questionnaire(UEQ) was also measured. The results show that the use of color on survey page has no significant differences with answering time and response rate. However, there are some scales of user experience have significant differences with the use of color on survey page. Advisors/Committee Members: Yi-Ling Lin (chair), Hsin-Hui Lin (committee member), Yih Jeng (chair).

Subjects/Keywords: user experience questionnaire; user experience; web survey; color; answering time; response rate

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chiang, M. (2017). The impact on answering time, response rate and user experience of using color on web survey. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025117-132409

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chiang, Meng-yuan. “The impact on answering time, response rate and user experience of using color on web survey.” 2017. Thesis, NSYSU. Accessed January 19, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025117-132409.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chiang, Meng-yuan. “The impact on answering time, response rate and user experience of using color on web survey.” 2017. Web. 19 Jan 2020.

Vancouver:

Chiang M. The impact on answering time, response rate and user experience of using color on web survey. [Internet] [Thesis]. NSYSU; 2017. [cited 2020 Jan 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025117-132409.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chiang M. The impact on answering time, response rate and user experience of using color on web survey. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025117-132409

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.