1. Jon Juett April 21, 2014

2.  Selected very recent papers  Includes some student level event / conference papers  UM Health Counseling Program  Correctly respond to emotion  Follow tree-based conversation  Detect deception, infer progress, etc.

3.  First automated system by Green et al in 1961  Early systems domain specific  Open domain problem initially too large  Internet makes more data sets available and searches more common  Database querying becomes faster  Open domain QA research resumes

4.  Computationally inexpensive  Current bottleneck in initial search  Can scale with dataset growth  Especially Internet  Fully automated  Except if cooperative steps with user included  Finds short, correct answers  User-friendly

5.  Like a Google Search  Uses primitive techniques  Bag of Words  Easier task  Returns entire likely relevant documents  Leaves answer extraction step to user

6.  In an open domain, cannot rely on domain specific knowledge  General world knowledge only  Conglomeration of components  Many systems overlap, plug-in techniques

7.  Cooperative Component  Not restricted to literal answers  Allows clarification of question for better answer  Can build up information on user interests, system may even lead conversation to do this

8.  Database approaches  Semantic via Resource Description Framework (RDF) Triples ▪ (subject, verb, object) ▪ Answer true/false or factoid ▪ Efficiently increase answer database  Template matching ▪ Use machine learning to cluster questions ▪ Templates can correct for typos and abbreviations ▪ Only need to store an answer to each cluster ▪ Novel questions matched to closest cluster

9. Question WordGoogle Answer RatioSemantic Web Answer Ratio What0.570.52 When0.850.90 Where0.830.95 Which0.500.15 Who0.770.66 How0.50 How old0.360.56 How long0.98 How many0.50 Najmi et al, 2013

10.  Response to unnatural feel of non-affective dialogue systems  Sense user emotional state  Punctuation, word choice, capitalization, emoticons  Simulate emotions  Speech synthesis, emoticons, nonverbal behavior  Attempt to influence user emotion  Extend to poll online communities  Composed of perception layer, control layer, and actuator-communicator layer

11.  Complex automated evaluation beyond state of the art  Multi-step reasoning  Real-time question answering  Language of user, query, data  Answer extraction  Customize to user preferences

12.  Fader, Anthony, Zettlemoyer, Luke, Etzioni, Oren, "Paraphrase-Driven Language for Open Question Answering," University of Washington ACL 2013.  Melo, Dora, Rodriues, Irene Pimenta, Nogueira, Vitor Beires, "A Review on Cooperative Question-Answering Systems," 2013.  Najmi, E.; Hashmi, K.; Khazalah, F.; Malik, Z., "Intelligent Semantic Question Answering System," Cybernetics (CYBCONF), 2013 IEEE International Conference on, vol., no., pp.255,260, 13-15 June 2013  Skowron, Marcin, "Affect Listeners: Acquisition of Affective States by Means of Conversational Systems," Development of Multimodal Interfaces: Active Listening and Synchrony, Springer Berlin Heidelberg, pp. 169-181 January 2010.  Tyagi, Deepali, Joshi, Tejas, Ghule, Dhanashri, Ameya, Joshi, "An Interactive Answering System using Template Matching and SQL Mapping for Natural Language Processing," International Journal of Advance Research in Computer Science and Management Studies, vol. 2, issue 2, pp. 165-168, February 2014