The ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR) provides a forum for the presentation and discussion of research related to the foundational aspects of Information Retrieval (IR), including, for example, human search processes; search and recommendation; learning and optimization for IR; language and representations for IR; sensory information related to IR; artificial intelligence, ethics and responsibility in information retrieval.

The conference explicitly welcomes papers on core IR and any paper on connections between IR and its neighboring disciplines. We welcome experimental and industrial papers that validate approaches from the lens of practical applicability. Such papers should, apart from validating the practical applicability of an existing approach, provide a clear message to the community as to which aspects need further (theoretical) investigation, based on the experimental findings.

Contributions could be:

    Theoretical papers that model various phenomena related to IR, and/or between concepts, models and theories;
    Conceptual papers that explore key concepts, new paradigms and new ways of thinking about problems in IR;
    Behavioral papers that explore the behavior of IR algorithms (why and how an algorithm works);
    Papers presenting preliminary work on exciting new ideas or approaches;
    Papers describing failed (but plausible!) approaches along with athorough analysis of what happened;
    Papers studying theory in experimental or industrial settings; or,
    Other papers that address foundational aspects of IR.

Topics

The topic areas covered by ICTIR include any topic of relevance to core IR and connections between IR and its neighboring disciplines such as the following. Evaluation expectations for ICTIR submissions are less demanding than in other IR conferences, but some degree of evaluation is still important.

IR theory and practice
New retrieval problems
Retrieval algorithm behavior analysis
Recommendation algorithm behavior analysis
Understanding IR models
Quantum IR or other non-conventional retrieval models and ranking
New evaluation measures, mathematical analysis of measures
New evaluation paradigms

User aspects of IR
Interactive and dynamic search
Information seeking
Modelling and simulation of information interaction
Contextual and personalized search
Search interfaces
Understanding context information
Understanding retrieval results
User modeling for ranking and evaluation

IR system architectures and scalability
Understanding IR system architecture
Efficient content representation
Compression for IR
String processing for IR
IR system scalability

Content representation and processing
Natural language processing for IR
Multimodal IR
Multilingual IR
Linguistic analysis
Text representation
Topic models

Machine learning for IR
Deep learning
Kernel methods
Markov decision processes
Online learning
Optimization
Hyper-parameter and model selection
Reinforcement learning

Applications of IR
Information extraction
Information fusion
Legal IR
Patent search
Search applied to the Internet of Things
Semantic search
Sentiment analysis
Social good and collaborative search
Voice and image search
Structured, semi-structured data and databases
Task-based and exploratory search
Web, digital libraries and social media search