Multilingual log analysis: LogCLEF

The current lack of recent and long-term query logs makes the verifiability and repeatability of log analysis experiments very limited. A first attempt in this direction has been made within the Cross-Language Evaluation Forum in 2009 in a track named LogCLEF which aims to stimulate research on user behaviour in multilingual environments and promote standard evaluation collections of log data. We report on similarities and differences of the most recent activities for LogCLEF

LogCLEF: Enabling research on multilingual log files

Interactions between users and information access systems can be analyzed and studied to gather user preferences and to learn what a user likes the most, and to use this information to adapt the search to users and personalize the presentation of results. The LogCLEF lab - ”A benchmarking activity on Multilingual Log File Analysis: Language identification, query classification, success of a query” deals with information contained in query logs of search engines and digital libraries from which knowledge can be mined to understand search behavior in multilingual context. LogCLEF has created the first long-term standard collection for evaluation purposes in the area of log analysis. The LogCLEF 2011 lab is the continuation of the past two editions: as a pilot task in CLEF 2009, and a workshop in CLEF 2010. The Cross-Language Evaluation Forum (CLEF) promotes research and development in multilingual information access and is an activity of the PROMISE Network of Excellence

The CLAIRE visual analytics system for analysing IR evaluation data

In this paper, we describe Combinatorial visuaL Analytics system for Information Retrieval Evaluation (CLAIRE), a Visual Analytics (VA) system for exploring and making sense of the performances of a large amount of Information Retrieval (IR) systems, in order to quickly and intuitively grasp which system configurations are preferred, what are the contributions of the different components and how these components interact together

Fourth International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse

© ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM SIGIR Forum (2011) http://doi.acm.org/10.1145/1988852.1988860[EN] The Fourth International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 10) was held in conjunction with the 2010 Conference on Multilingual and Multimodal Information Access Evaluation (CLEF-10) in Padua, Italy. The workshop was organized as a competition covering two tasks: plagiarism detection and Wikipedia vandalism detection. This report gives a short overview of the plagiarism detection task. Detailed analyses of both tasks have been published as CLEF Notebook Papers [3, 6], which can be downloaded at www.webis.de/publications.Our special thanks go to the participants of the competition for their devoted work. We also thank Yahoo! Research for their sponsorship. This work is partially funded by CONACYTMexico and the MICINN project TEXT-ENTERPRISE 2.0 TIN2009-13391-C04-03 (Plan I+D+i).Stein, B.; Rosso, P.; Stamatatos, E.; Potthast, M.; Barrón Cedeño, LA.; Koppel, M. (2011). Fourth International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse. ACM SIGIR Forum. 45(1):45-48. https://doi.org/10.1145/1988852.1988860S454845

Multilingual adaptive search for digital libraries

This paper describes a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both Adaptive and Multilingual IR, with a particular focus on Digital Libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user’s experience with online Digital Libraries

A linguistic failure analysis of classification of medical publications: A study on stemming vs lemmatization

Technology-Assisted Review (TAR) systems are essential to minimize the effort of the user during the search and retrieval of relevant documents for a specific information need. In this paper, we present a failure analysis based on terminological and linguistic aspects of a TAR system for systematic medical reviews. In particular, we analyze the results of the worst performing topics in terms of recall using the dataset of the CLEF 2017 eHealth task on TAR in Empirical Medicine.I sistemi TAR (Technology-Assisted Review) sono fondamentali per ridurre al minimo lo sforzo dell’utente che intende ricercare e recuperare i documenti rilevanti per uno specifico bisogno informativo. In questo articolo, presentiamo una failure analysis basata su aspetti terminologici e linguistici di un sistema TAR per le revisioni sistematiche in campo medico. In particolare, analizziamo i topic per i quali abbiamo ottenuto dei risultati peggiori in termini di recall utilizzando il dataset di CLEF 2017 eHealth task on TAR in Empirical Medicine

Late Semantic Fusion Approach for the Retrieval of Multimedia Data

In Multimedia information retrieval late semantic fusion is used to combine textual pre-filtering with an image re-ranking. Three steps are used for retrieval processes. Visual and textual techniques are combined to help the developed Multimedia Information Retrieval System to minimize the semantic gap for given query. In the paper, different late semantic fusion approaches i.e. Product, Enrich, MaxMerge and FilterN are used and for experiments publicly available ImageCLEF Wikipedia Collection is used. DOI: 10.17762/ijritcc2321-8169.150610