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Information Retrieval Journal 

Special Issue on eCommerce Search and Recommendation - Call For Papers : https://bit.ly/2H7FarY <https://bit.ly/2H7FarY>

Important Dates:
Initial submissions due: December 15, 2018 
Initial reviewer feedback: February 15, 2019 
Revised submission due: April 15, 2019 
Final reviews and notification: May 15, 2019
Search, ranking and recommendations have applications ranging from traditional web search to document databases to vertical search systems. In this special issue we will explore approaches for search and recommendations of products, as well as other aspects of eCommerce Information Retrieval.
Topics of interest
Scope

The special issue relates to all aspects of eCommerce search and recommendation. Research topics and challenges that are usually encountered in this domain include (but are not limited to):

System architecture
Algorithms for ranking and recommendation
Machine learning techniques such as online learning and deep learning for eCommerce applications
Semantic representation for users, products and services & semantic understanding of queries
Structured data and faceted search
The use of domain specific facets in search and other IR tasks
Temporal dynamics for search and recommendation
Models for relevance and ranking for multi-faceted entities
Deterministic (and other) sorting of results lists (e.g. price low to high including postage)
Personalized search and recommendations
Session aware and session oriented search and recommendations
Inventory display issues (example: legal, ethical, and spam)
Cold start issues and approaches to addressing cold start
Personalization and the use of personal facets such as age, gender, location etc.
Indexing efficiency incorporating structured product data and catalog information
Indexing and search in a rapidly changing environment (for example, an auction site)
Scalability
Diversity in product search and recommendations
Strategies for resolving extremely low (or no) recall queries
Query intent
Semantic understanding of queries
The use of external features such as reviews and ratings in ranking
User interfaces and personalization
Reviews and sentiment analysis
The use of social signals in ranking and beyond
The balance between business requirements and user requirements (revenue vs relevance)
Trust
Live experimentation 
Desktop and mobile issues
Questions and answering, chatbots for eCommerce
Transfer learning and multi-task learning applications in eCommerce
Conversational commerce: shopping using voice assistants such as Amazon Alexa and Google Now
Fashion eCommerce

Special Issue Guest Editors
Jon Degenhardt, eBay inc., USA
Surya Kallumadi,  Kansas State University, USA
Andrew Trotman,  University of Otago, New Zealand (contact: [log in to unmask] <mailto:[log in to unmask]>)
Important Dates:
Initial submissions due: December 15, 2018 
Initial reviewer feedback: February 15, 2019 
Revised submission due: April 15, 2019 
Final reviews and notification: May 15, 2019
Paper Submission instructions:

Papers submitted to the special issue must be original, and must not be under consideration for publication anywhere else. Data that have already been used in previously published work can only be reused if the research questions and analysis framework are new. 

All papers are to be submitted by referring to http://www.springer.com/10791 <http://www.springer.com/10791> (submit online).
At the beginning of the submission process in Editorial Manager, under “Article Type”, please select the appropriate special issue.

All manuscripts must be prepared according to the journal publication guidelines which can also be found on the website provided above. Papers will be evaluated following the journal's standard review process. 

For inquiries on the above please contact Andrew Trotman ([log in to unmask] <mailto:[log in to unmask]>).


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