SIGIR-AP 2023 : 1st International ACM SIGIR Conference on Information Retrieval in the Asia Pacific
Call For Papers
The anual SIGIR-AP (Asia/Pacific) conference is a new regional IR conference whose scope is fundamentally the same as that of SIGIR. It will be hybrid, so authors of accepted papers can either present their work in-person or remotely.
The conference adopts double-blind, single-track reviewing, and allows submissions of papers that are commensurate with contribution size. Specifically, there are two types of SIGIR-AP submissions: Regular submissions and SIGIR-Revise-and-Resubmit submissions.
Regular submissions are new, original contributions that have not been submitted elsewhere before. We also welcome Resource papers and Reproducibility papers. Resources papers consider test collections and labelled datasets, designs and protocols of evaluation tasks, and software tools and services for information access. Reproducibility papers repeat, reproduce, generalize, and reexamine prior work, for example analysing to what extent assumptions of the original work are valid, or identify error modes and unexpected conclusions; typically these papers involve a new team and a new experimental setup, that is, they go beyond replication.
Format: Paper body + references
Paper body should be 2-9 pages, and be commensurate with contribution size.
References have no page limit.
SIGIR-Revise-and-Resubmit (SIGIR-RR) Submissions
SIGIR-RR submissions are revised versions of either full or short papers that were not accepted at the immediately preceding SIGIR conference (this option is not available for other SIGIR paper tracks, e.g., perspectives, resource, or reproducibility). In addition to the revised paper, the authors must include in the submission file a text explaining the revision based on the SIGIR reviews, as well as the original SIGIR submission.
Format: Paper body + References + Explanation (with SIGIR paper ID) + SIGIR submission
Paper body should be 2-9 pages, and be commensurate with contribution size.
References have no page limit.
Explanation (1-3 pages, no style requirements): a SIGIR paper ID, plus a text that explain how the authors addressed the points raised by the SIGIR reviewers after the SIGIR rejection.
SIGIR submission include the original anonymised SIGIR submission as is in the SIGIR-AP submission. .
Important dates for paper submission:
Time zone: Anywhere On Earth (AOE)
Abstracts due: June 26, 2023
Paper submission due: July 3, 2023
Paper decision notifications: September 10, 2023
Camera ready papers due: September 26, 2023
All papers must be original and not simultaneously submitted to another journal or conference.
Submissions of regular and SIGIR-RR papers must be in English, in PDF format, be at least 2 pages and at most 9 pages (including figures) + unlimited pages for references in length, in the current ACM two-column conference format. Each paper will be accessed according to whether the paper length is commensurate with contribution size. That is, for example, if a paper contains a good scientific contribution that is worth 2 pages, then that 2-page paper should be a candidate for acceptance; if a 9-page paper does not contain enough substance, then the paper is considered weak. Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website (use the“sigconf”proceedings template). Papers must describe work that is not previously published, not accepted for publication elsewhere, and not currently under review elsewhere. Submissions must be anonymous and should be submitted electronically via the conference submission system.
Authors are required to take all reasonable steps to preserve the anonymity of their submission. The submissions document must not include author information and must not include citations or discussion of related work that would make the authorship apparent. Note however, that it is acceptable to explicitly refer in the paper to the companies or organizations that provided datasets, hosted experiments, or deployed solutions. For example, instead of stating that an experiment “was conducted on the logs of a major search engine”, the authors should refer to the search engine by name. The reviewers will be informed that it does not necessarily imply that the authors are currently affiliated with the mentioned organization. While authors can upload to institutional or other preprint repositories such as arXiv.org before reviewing is complete, we generally discourage this since it places anonymity at risk (which could result in a negative outcome of the reviewing process). Authors should carefully go through ACM’s authorship policy before submitting a paper. To support identification of reviewers with conflicts of interest, the full author list must be specified at submission time. Authors should note that changes to the author list after the submission deadline are not allowed without permission from the PC Chairs. At least one author of each accepted paper is required to register for, attend, and present the work at the conference.
All papers are to be submitted via
GUIDANCE FOR AUTHORS
To ensure the quality of submissions, we also provide a guidance for authors. We recommend that authors observe the guidance in preparing their papers.
TOPICS OF INTEREST
Relevant topics include, but are not limited to:
Search and Ranking:
Research on core IR principles and algorithms, such as:
Queries and query analysis (e.g., query intent, query understanding, query suggestion and prediction, query representation and reformulation, spoken queries).
Web search (e.g., ranking at web scale, link analysis, sponsored search, search advertising, adversarial search and spam, vertical search).
Retrieval models and ranking (e.g., ranking algorithms, learning to rank, language models, retrieval models, combining searches, diversity, aggregated search, dealing with bias)
Efficiency and scalability (e.g., indexing, crawling, compression, search engine architecture, distributed search, metasearch, peer-to-peer search, search in the cloud).
Information security (e.g., encryption, sharing protocols, privacy guarantees).
Theoretical models and foundations of information retrieval and access (e.g., new theory, fundamental concepts, theoretical analysis).
Search, Recommendation, and Content Analysis for Search and Recommendation:
Research focusing on recommender systems, rich content representations and content analysis, such as:
Filtering and recommendation (e.g., content-based filtering, collaborative filtering, recommender systems, recommendation algorithms, zero-query and implicit search, personalized recommendation).
Document representation and content analysis for search or recommendation (e.g., cross-lingual and multilingual search, NLP: summarization, text representation, linguistic analysis, readability, opinion mining and sentiment analysis, clustering, classification, topic models for search and recommendation).
Knowledge acquisition (e.g., information extraction, relation extraction, event extraction, query understanding, human-in-the-loop knowledge acquisition).
Machine Learning and Natural Language Processing for Search and Recommendation:
Research bridging ML, NLP, and IR, such as:
Core ML (e.g., deep learning for IR, embeddings, intelligent personal assistants and agents, unbiased learning).
Question answering (e.g., factoid and non-factoid question answering, interactive question answering, community-based question answering, question answering systems).
Conversational systems (e.g., conversational search interaction, dialog systems, spoken language interfaces, intelligent chat systems).
Explicit semantics (e.g., semantic search, named-entities, relation and event extraction).
Knowledge representation and reasoning (e.g., link prediction, knowledge graph completion, knowledge-guided query and document representation, ontology modeling).
Humans and Interaction:
Research into user-centric aspects of IR including user interfaces, behavior modeling, interactive systems, such as:
Mining and modeling users (e.g., user and task models, click models, log analysis, behavioral analysis, modeling and simulation of interaction, modeling of cognition).
Interactive search (e.g., search interfaces, information access, exploratory search, search context, whole-session support, proactive search, personalized search).
Collaborative search (e.g., human-in-the-loop, knowledge acquisition, social tagging, crowdsourcing).
Information security (e.g., privacy, surveillance, censorship, encryption).
User studies (e.g., learning during search, behaviours in search and recommendation).
Research that focuses on the measurement and evaluation of IR systems, such as:
User-centered evaluation (e.g., user experience and performance, user engagement, search task design).
System-centered evaluation (e.g., evaluation metrics, test collections, experimental design, evaluation pipelines, crowdsourcing).
Beyond Cranfield (e.g., online evaluation, task-based, session-based, multi-turn, interactive search).
Beyond labels (e.g., simulation, implicit signals, eye-tracking and physiological signals).
Beyond effectiveness (e.g., value, utility, usefulness, diversity, novelty, urgency, freshness, credibility, authority).
Methodology (e.g., statistical methods, reproducibility, dealing with bias, new experimental approaches, metrics for metrics).
Fairness, Accountability, Transparency, Ethics, and Explainability (FATE) in IR:
Research on aspects of responsibility, fairness, and bias in search and recommender systems, such as:
Fairness, accountability, transparency (e.g., confidentiality, representativeness, discrimination and harmful bias).
Ethics, economics, and politics (e.g., studies on broader implications, norms and ethics, economic value, political impact, social good).
Two-sided search and recommendation scenarios (e.g., matching users and providers, marketplaces).
Personal safety (e.g., anonymisation, privacy principles, surveillance, censorship).
Research focusing on domain-specific IR challenges, such as:
Local and mobile search (e.g., location-based search, mobile usage understanding, mobile result presentation, audio and touch interfaces, geographic search, location context in search).
Social search (e.g., social networks in search, social media in search, blog and microblog search, forum search, Q&A repositories).
Search in structured data (e.g., XML search, graph search, ranking in databases, desktop search, email search, entity-oriented search).
Xuanjing Huang, Fudan University, P. R. China
Tetsuya Sakai, Waseda University, Japan
Justin Zobel, University of Melbourne, Australia