-------- Forwarded Message -------- Subject: [AISWorld] [Deadline is approaching] International Workshop on Technologies for Information Retrieval (TIR'19) Date: Tue, 02 Apr 2019 11:17:46 +0200 From: Hesti Sudjana hesti.sudjana@jku.at To: aisworld@lists.aisnet.org
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C A L L F O R P A P E R S
The 16th International Workshop on Technologies for Information Retrieval (TIR'19)
Linz, Austria August 26 - 29, 2019
https://webis.de/tir/tir-19/ Email: tir@webis.de Paper submission: https://confdriver.ifs.tuwien.ac.at/dexa2019 All accepted papers will be published in Communications in Computer and Information Science (CCIS)by Springer
***** IMPORTANT DATES ***** - Submission deadline: April 05, 2019 (23:59 CET) - Notification of acceptance: May 23, 2019 - Camera-ready copies due: June 08, 2019
***** PUBLICATION ***** Accepted papers will be published by Springer in "Communications in Computer and Information Science - CCIS".
***** SCOPE ***** The development of advanced retrieval solutions requires the understanding and the combination of methods from different research areas, including machine learning, (big) data mining, natural language processing, artificial intelligence, user interaction and modeling, and Web engineering. In addition, societal challenges such as information quality, bias, or the trustworthiness of the stated facts and arguments have come into focus.
The TIR workshop is held for the sixteenth time. Past workshops could attract high-quality and innovative contributions and were characterized by an open and stimulating atmosphere.
***** TOPICS ***** In this regard the TIR workshop provides a platform for presenting and discussing new solutions, novel ideas, or specific tools for future retrieval and text understanding systems. The following list organizes classic and recent topics for which contributions are welcome, but not limited to: - Theory. Retrieval models, similarity measures, formal analysis - Evaluation. Corpus construction, experiment design, performance measures, reproducibility, benchmarking of Information Retrieval and Machine Learning algorithms - Information Quality and Provenance. Text quality assessment, text reuse, trust and author reputation, provenance analytics - Natural Language Technologies for IR Applications. Opinion mining, text summarization and simplification, question answering, discourse and argument mining - Personalization. Personalized retrieval, context detection, user profiling, user modeling - Web Search. Ranking and recommendation, query classification and segmentation, vertical search, dynamic taxonomy generation - Social Media Analytics. People analytics, social network analysis, trend analysis - Semantic Web. Meta data analysis and tagging, knowledge extraction, inference and linking - Machine Learning. Representation learning for text mining - Explanations. Explainable IR models, result explanations, evaluation of explanations
***** SUBMISSION GUIDELINES ***** - Submissions to TIR 2019 must be original, unpublished contributions and must not be under submission elsewhere. - Papers must be written in English and are limited to 5 pages - Formatting guidelines refer to http://www.dexa.org/formatting_guidelines - Submission is made electronically in PDF format using our conference management system (http://www.dexa.org/paper_submission) - Submitted papers will be peer-reviewed by at least three experts from the related field. - At least one author of each accepted paper is required to register for the DEXA'19 conference, attend the TIR'19 workshop, and present the paper.
***** PAST WORKSHOPS ***** https://webis.de/events.html#tir-workshop-series
***** PC Co-chairs ***** Christin Seifert, University of Twente, The Netherlands Benno Stein, Bauhaus-Universität Weimar, Germany Michael Granitzer, University of Passau, Germany
***** PC MEMBERS ***** https://webis.de/tir/tir------------------------------------------------- Hesti Sudjana Telecooperation Departement Johannes Kepler University Linz Science Park 3, Altenberger Straße 69, 4040 Linz, Austria -------------------------------------------------
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