'Project Hal'
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Daden Emerging Technology Seminar - Introduction to Chatbots & their uses within a business - Guest Speaker John Dowd from University of Wolverhampton talks about Chatbots.
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'Project Hal'
- 1. Project HAL Agenda: 1. Who 2. Why 3. What 4. W Outcomes
- 2. WHO The Numbers. 150 Years Applied Sciences Art & Design Business 8 Schools Education 4 Campuses Health & Wellbeing Law, Social Sciences & Communication Sport, Performing Arts & Leisure Technology 23,000 Students
- 3. WHO WHO Strategic Plan, 2009 12 From fixed to flexible From print to electronic From physical to virtual
- 4. 安鞄霞 Where Do I Click Now?
- 6. WHAT Supportive role with regards to the Web Refresh project Development of an evidence based FAQ A push to web site content not being fully utilised An adjunct to ASSIST (project) Alternate front-end/access method to content on LIS website Interactive vs Passive LISs chatbot is an interface which will provide real-time interaction and navigation to resources and services provided by LIS. It supplements the ASSIST online chat service, by dealing with routine information enquiries. enquiries Created: 24th October 08
- 7. WHAT WHAT
- 8. WHAT WHAT WHAT Criteria Lightweight, Easily Controllable Chatbot database to extract responses from FAQ on web site Chatbot database to be maintained by export of FAQ database to file, then import into Chabot Chatbot configured to refer to relevant pages of Website Chatbot database to be standalone with full configuration of all questions/responses
- 12. 安O雨意遺或珂掘皆 Pre-launch Testing August 2009
- 13. Quantitative Chatbot Versus Assist % of Correct & Incorrect Answers 48% Correct 52% Incorrect
- 14. Qualitative Chatbot Versus People Did you find the chatbot helpful? 85% (score 4 out of 5) Did you enjoy using the chatbot? 80% Would you use it again? 60% yes/20% maybe Have you used ASSIST before? 40% yes Would you use the chatbot first in future? 100% yes How many questions did the bot get right? = 16 out of 19
- 15. Additional from survey: What did you like about it? Appearance helpful Ability to ask the question using natural lively language, not just a key words like it is when enjoyable service 油 using search engines Answer was told and written 油 instant answer quick answers, links you straight to the page you need, points you in the right direction reads out the answer as well as it being typed at the it would be useful to new students 油 side. 油 more personal without having to talk to a person, accessible from home, gives good information 油
- 16. What didnt you like about it? voice was annoying, is a white librarian going to be good for all students? does it come in other languages? 油 The lady at the start talking made me jump! *the bot said hello I am harry but she was a girl Whether students would bother using the chatbox *sounded a bit rude when it did not understand the question How students would find chatbox on the web im dyslexic and i found it slightly hard to word questions to explain what i meant so it would understand. When I first used the chatbot, I didn't expect it to open the webpage, but to give me an answer. I asked the question and it said "See if this page contains information you require", I was confused, because I expected the information will be given by a chatbot, not that I will be redirected to the webpage. It advised me to contact Learning Centre Direct, but didn't open the webpage with contact details.
- 17. Other comments It has some problems with understanding long sentences, but generally works very well. It's much more user-friendly way of finding information on the website than search engines. .. . My personal favourite think it's a really good idea because it takes you to pages on the internet you might never have come across or been aware of. im in third year and still dont understand how ejournals work but it took me to a page that explained everything.
- 18. Controlled Launch -Semester 2 - January 2010
- 19. Quantitative 350 300 250 28% 200 Correct Incorrect 150 Answered correctly 100 Answered incorrectly 50 72% 0 January February March April May June
- 20. Patterns 40 ASSIST Queries (Comparative Review) 35 SEPT 250 OCT 30 NOV 200 DEC 25 JAN FEB 20 150 MAR APR 15 100 MAY 10 JUNE JULY 50 5 AUG 00 January February March April May June 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 700 No. of chatbot chat sessions by time 600 45 40 500 35 400 30 No. of chats 25 300 20 200 15 10 100 5 0 0 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00 22.00 23.00 January February March April May June Time (24 hr clock)
- 21. Qualitative
- 22. Comments