Connectionists: Deadline Extension: WSDM Workshop on Learning from User Interactions (8th December)

[Rishabh Mehrotra]

*WSDM Workshop on Learning from User Interactions*

We invite contributions to WSDM Workshop on Learning from User Interactions
<https://task-ir.github.io/wsdm2018-learnIR-workshop/> at WSDM 2018
<http://www.wsdm-conference.org/2018/> to be held in Los Angeles, 6 - 8 Feb
2018.

*TL;DR**:* 4-6 pages, in WSDM format, *submit by December 8th (23:59 AOE
time)*.

Workshop Website: https://task-ir.github.io/wsdm2018-learnIR-workshop/
Submission Link: Easychair
<https://easychair.org/conferences/?conf=learnir2018>
Twitter: https://twitter.com/learnIRWSDM

We intend to have a sponsored Best Paper award alongside potential
registration support for students.
*Overview*

While users interact with online services (e.g. search engines, recommender
systems, conversational agents), they leave behind fine grained traces of
interaction patterns. The ability to understand user behavior, record and
interpret user interaction signals, gauge user satisfaction and incorporate
user feedback gives online systems a vast treasure trove of insights for
improvement and experimentation. More generally, the ability to learn from
user interactions promises pathways for solving a number of problems and
improving user engagement and satisfaction.

Understanding and learning from user interactions involves a number of
different aspects - from understanding user intent and tasks, to developing
user models and personalization services. A user's understanding of their
need and the overall task develop as they interact with the system.
Supporting the various stages of the task involves many aspects of the
system, e.g. interface features, presentation of information, retrieving
and ranking. Often, online systems are not specifically designed to support
users in successfully accomplishing the tasks which motivated them to
interact with the system in the first place. Beyond understanding user
needs, learning from user interactions involves developing the right
metrics and expiermentation systems, understanding user interaction
processes, their usage context and designing interfaces capable of helping
users.

Learning from user interactions becomes more important as new and novel
ways of user interactions surface. There is a gradual shift towards
searching and presenting the information in a conversational form.
Chatbots, personal assistants in our phones and eyes-free devices are being
used increasingly more for different purposes, including information
retrieval and exploration. With improved speech recognition and information
retrieval systems, more and more users are increasingly relying on such
digital assistants to fulfill their information needs and complete their
tasks. Such systems rely heavily on quickly learnig from past interactions
and incorporating implicit feedback signals into their models for rapid
development.

Topics

Learning from User Interactions will be a highly interactive full day
workshop that will provide a forum for academic and industrial researchers
working at the intersection of user understanding, search tasks,
conversational IR and user interactions. The purpose is to provide an
opportunity for people to present new work and early results, brainstorm
different use cases, share best practices, and discuss the main challenges
facing this line of research.


   - User Needs & Tasks Understanding:
      - User intent analysis/prediction
      - User goals & missions
      - Task identification
      - Task aware suggestions & recommendations

   - User Modeling & Personalization:
      - Short and Long-term User Modelling
      - Personalization
      - Diversification
      - Coherence

   - Metrics and Evaluation :
      - Metrics based on user interactions
      - User engagement metrics design
      - Evaluation mechanisms
      - User satisfaction prediction
      - Controlled laboratory study
      - Online metrics
      - Test collection

   - User Interaction Processes & Context :
      - User Journey Optimization
      - Evolution of search process
      - Stages of user interactions
      - User journey through the system
      - Leveraging contextual signals
      - Learning for user interaction optimization: algorithms, frameworks
      & system designs

   - Intelligent interface designs:
      - Adaptive personal digital assistants
      - Tailored decision support
      - Adaptive collaboration support

   - Applications:
      - Conversational search, chatbots, digital assistants
      - Contextual Advertising
      - E-commerce recommendations
      - Customer Support
      - Intelligent interfaces
      - Personal search
      - Case studies of real world implementations

Submission

All workshop submissions must be formatted according to ACM SIG Proceedings
<http://www.acm.org/publications/proceedings-template>template. We welcome
submissions in either long or short format spanning 4-6 pages.

Authors should submit original papers in PDF format through the Easychair
system <https://easychair.org/conferences/?conf=learnir2018>.

This is a workshop where discussion is central, and all attendees are
active participants. The workshop will include keynote talks to set the
stage and ensure all attendees are on the same page. A small number of
contributed papers will be selected for short oral presentation (15-10
minutes), all other papers have a 2 minute boaster, and all papers are
presented as poster in an interactive poster session.

The results will be disseminated in various ways:

   - A high quality, peer reviewed workshop proceedings, published in the
   http://ceur-ws.org/ workshop proceedings series.
   - A report on the results of the workshop in the ACM SIGIR Forum of June
   2018.
   - If the outcome lives up to our high expectations, we will consider a
   special issue in an appropriate journal.


Important Dates

   - Submission Deadline: 8th December 2017 (23:59 AOE)
   - Notification: 15th December 2017
   - Workshop: 9th February 2018


Organizers

   1.

   Rishabh Mehrotra <http://www.rishabhmehrotra.com/> (Spotify Research;
   University College London)
   2.

   Emine Yilmaz <https://sites.google.com/site/emineyilmaz/> (University
   College London; The Alan Turing Institute)
   3.

   Ahmed Hassan Awadallah
   <http://research.microsoft.com/en-us/um/people/hassanam/> (Microsoft
   Research)

You can contact us at learnIRwrkshp at gmail.com <learnirwrkshp at gmail.com> or
at erishabh at gmail.com.

Steering Committee:

- Milad Shokouhi <https://www.microsoft.com/en-us/research/people/milads/>
 (Microsoft)
- Fernando Diaz <http://fernando.diaz.nyc/> (Spotify)
- Filip Radlinski <http://radlinski.org/> (Google Research)
- Evangelos Kanoulas <https://staff.fnwi.uva.nl/e.kanoulas/> (University of
Amsterdam)

-- 
Rishabh.
Web: www.rishabhmehrotra.com
Github: https://github.com/rishabhmehrotra/
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