CLEF

This paper describes our participation to the Entrance Ex- ams Task of CLEF 2014's Question Answering Track. The goal is to an- swer multiple-choice questions on short texts. Our system rst retrieves passages relevant to the question, through lexical expansion involving a structured use of the Simple English Wiktionary and WordNet. Then it extracts predicate-argument structures (PAS) from each answer choice and aligns them to PAS found in the passages retrieved in the rst step. Finally, manually crafted rules are applied to those alignments to try to invalidate answer choices. If enough answer choices are thus invalidated, we make a decision on the remaining answer choices based on their align- ment scores with the passages. We submitted several runs in the task, only one of which reached the random baseline (c@1 of 0.25). In the last section, we provide an analysis of the dierences between our relatively good results obtained on trial data and the poor performance of our test run.

This paper provides a comprehensive overview of Task 3 of the CLEF 2024 JOKER track on automatic houmous analysis. The overarching objective of the JOKER track series is to facilitate collaboration among linguists, translators, and computer scientists to advance the development of automatic interpretation, generation, and translation of wordplay. Task 3 specifically concentrates on the automatic translation of puns from English into French. This overview outlines the overall structure of the shared task we organised as part of the CLEF 2024 evaluation campaign. We discuss the approaches employed by the participants and present and analyse the results they achieved. We also describe the work of participants who used our data to translate puns from English to Spanish as part of the open task of the track.

This paper deals with lexicon and system development for word segmentation in Bangla language.Our goal in this paper is to develop a morphological segmentation algorithm that can work well for Bangla and to address the problem of unsupervised word segmentation across different languages.From a hand-corrected Bangla corpus, 5000 popular words were segmented into suffixes, prefixes and roots manually.These were the sample lexicon used as seed for next step. A system was developed using C language to automate the Segmentation process based on hand made lexical database.The System was evaluated on several pages of Bangla text and achieved a success rate of about 83.05%.In our observation the system will work with full success if twice the volume of lexicon database and this system may have a huge impact particularly to learn and use Bangla for the people which will enhance their socio-economic life greatly.

This review summarizes recent advances in micro- and nanopore technologies with a focus on the functionalization of pores using a promising method named contactless electro-functionalization (CLEF). CLEF enables the localized grafting of electroactive entities onto the inner wall of a micro- or nano-sized pore in a solid-state silicon/silicon oxide membrane. A voltage or electrical current applied across the pore induces the surface functionalization by electroactive entities exclusively on the inside pore wall, which is a significant improvement over existing methods. CLEF’s mechanism is based on the polarization of a sandwich-like silicon/silicon oxide membrane, creating electronic pathways between the core silicon and the electrolyte. Correlation between numerical simulations and experiments have validated this hypothesis. CLEF-induced micro- and nanopores functionalized with antibodies or oligonucleotides were successfully used for the detection and identification of cells and a...

Penemuan tentang biologi menyebabkan semakin banyaknya objek yang harus dipelajari dari Biologi, sehingga seorang ilmuwan tidak sanggup lagi mempelajari secara mendalam seluruh objek kajian Biologi. Maka dari itu, cabang-cabang Biologi dikembangkan untuk mempermudah mempelajari masing- masing kajian objek Biologi. Di dalam modul ini akan dijelaskan ruang lingkup biologi (permasalahan pada berbagai objek biologi dan tingkat organisasi kehidupan), melalui penerapan metode ilmiah dan prinsip keselamatan kerja

Abstract. This paper describes the Question Answering for Machine Reading (QA4MRE) task at the 2012 Cross Language Evaluation Forum. In the main task, systems answered multiple-choice questions on documents concerned with four different topics. There were also two pilot tasks, Processing Modality and Negation for Machine Reading, and Machine Reading on Biomedical Texts about Alzheimer's disease. This paper describes the preparation of the data sets, the definition of the background collections, the metric used for the evaluation of the systems ’ submissions, and the results. Eleven groups participated in the task submitting a total of 43 runs in seven languages. 1.

In this working notes report/paper, we describe the details of two submis- sions for CLEF 2015 eHealth challenge for Task 1a, with details of methods and tools developed for automatic speech recognition of NICTA synthetic nursing handover dataset. The first method involves a novel zero-resource approach based on unsuper- vised acoustic only modeling of speech involving word discovery, and the second method is based on combination of acoustic, language, grammar and dictionary models, using well known open source speech recognition toolkit from CMU, the CMU Sphinx(7). The experimental evaluation of the two methods was done on Challenge dataset (NICTA synthetic nursing handover dataset).

In this article, we present a factoid question-answering system, Sibyl, specifically tailored for question answering (QA) on spoken-word documents. This work explores, for the first time, which techniques can be robustly adapted from the usual QA on written documents to the more difficult spoken document scenario. More specifically, we study new information retrieval (IR) techniques designed or speech, and utilize several levels of linguistic information for the speech-based QA task. These include named-entity detection with phonetic information, syntactic parsing applied to speech transcripts, and the use of coreference resolution. Sibyl is largely based on supervised machine-learning techniques, with special focus on the answer extraction step, and makes little use of handcrafted knowledge. Consequently, it should be easily adaptable to other domains and languages. Sibyl and all its modules are extensively evaluated on the European Parliament Plenary Sessions English corpus, compa...

This paper presents LIMSI’s participation in the User-Centered Health Information Retrieval task (task 2) at the CLEF eHealth 2015 workshop. In our contribution we explored two different strategies to query expansion, i.e. one based on entity recognition using MetaMap and the UMLS, and a second strategy based on disease hypothesis generation using self-constructed external resources such a corpus of Wikipedia pages describing diseases and conditions, and web pages from the Medline Plus health portal. Our best-scoring run was a weighed UMLS-based run which put emphasis on incorporating signs and symptoms recognized in the topic text by MetaMap. This run achieved a P@10 score of 0.262 and nDCG@10 of 0.196, respectively.

We present an overview of Task 1 of the fourth edition of the CheckThat! Lab, part of the 2021 Conference and Labs of the Evaluation Forum (CLEF). The task asks to predict which posts in a Twitter stream are worth fact-checking, focusing on COVID-19 and politics in five languages: Arabic, Bulgarian, English, Spanish, and Turkish. A total of 15 teams participated in this task and most submissions managed to achieve sizable improvements over the baselines using Transformer-based models such as BERT and RoBERTa. Here, we describe the process of data collection and the task setup, including the evaluation measures, and we give a brief overview of the participating systems. We release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research in check-worthiness estimation for tweets and political debates. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 Internatio...

This paper describes the participation of the INAOE's research group on machine learning for image processing and information retrieval from México. This year we proposed two approaches for the photographic retrieval task. First, we studied the annotation-based expansion of documents for image retrieval. This approach consists of automatically assigning labels to images by using supervised machine learning techniques. Labels are used for expanding the manual annotations of images. Then, we build a text-based ...

The paper reports our experiments in tackling the CLEF 2012 Pilot Task on Machine Reading for Question Answering. We introduce the technique of index expansion, which relies on building a search index enriched with information gathered from a linguistic analysis of texts. The index provides a highly tangled representation of the sentences where each word is directly connected to others representing both meaning and relations. Instead of keeping the knowledge base separate, the relevant knowledge gets embedded within the text. We can hence use efficient indexing techniques to represent such knowledge and query it very effectively. We explain how index expansion was used in the task and describe the experiments that we performed. The results achieved are quite positive and a final error analysis shows how the technique can be further improved.

Abstract. The article presents the experiments carried out as part of the participation in the Paragraph Selection (PS) Task and Answer Selection (AS) Task of QA@ CLEF 2010–ResPubliQA. Our System use Apache Lucene for document retrieval system. All test documents are indexed using Apache Lucene. Stop words are removed from each question and query words are identified to retrieve the most relevant documents using Lucene. Relevant paragraphs are selected from the retrieved documents based on the TF-IDF of ...