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MEduKG: A Deep-Learning-Based Approach for Multi-Modal Educational Knowledge Graph Construction
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In: Information; Volume 13; Issue 2; Pages: 91 (2022)
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Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2298 (2022)
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Prediction and Visual Intelligence for Security Information: The PREVISION H2020 Project
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In: CIRCLE 2020 ; https://hal.archives-ouvertes.fr/hal-02877780 ; CIRCLE 2020, Iván Cantador; Max Chevalier; Massimo Melucci; Josiane Mothe, Jul 2020, Samatan, France ; http://ceur-ws.org/Vol-2621/ (2020)
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Multimodal deep networks for text and image-based document classification ; Réseau de neurones multimodal pour la classification de documents image/texte
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In: Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle (APIA) ; https://hal.archives-ouvertes.fr/hal-02163257 ; Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle (APIA), Jul 2019, Toulouse, France (2019)
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Data Fusion through Fuzzy-Bayesian Networks for Belief Generation in Cognitive Agents
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In: Revista de Informática Teórica e Aplicada; v. 26, n. 2 (2019); 69-80 ; 21752745 ; 01034308 (2019)
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Methodology for automatic bioacoustic classification of anurans based on feature fusion
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In: Expert Systems With Applications[ISSN 0957-4174],v. 50, p. 100-106 (2016)
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Disambiguation of Named Entities in Cultural Heritage Texts Using Linked Data Sets
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In: New Trends in Databases and Information Systems ; First International Workshop on Semantic Web for Cultural Heritage, SW4CH 2015 ; https://hal.archives-ouvertes.fr/hal-01203784 ; First International Workshop on Semantic Web for Cultural Heritage, SW4CH 2015, Sep 2015, Poitiers, France. pp.505-514, ⟨10.1007/978-3-319-23201-0_51⟩ (2015)
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| 9 |
Mobile Active Authentication via Linguistic Modalities
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In: DTIC (2015)
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A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules
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| 11 |
Aging time and brand determination of pasteurized milk using a multisensor e-nose combined with a voltammetric e-tongue
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In: ISSN: 0928-4931 ; Materials Science and Engineering: C ; https://hal.archives-ouvertes.fr/hal-01073780 ; Materials Science and Engineering: C, Elsevier, 2014, 45, pp.348-358. ⟨10.1016/j.msec.2014.09.030⟩ (2014)
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| 12 |
Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment
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| 13 |
Face Recognition and Event Detection in Video: An Overview of PROVE-IT Projects
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| 14 |
Towards a Simple and Efficient Web Search Framework
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In: DTIC (2014)
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| 15 |
On the Design of an Intelligent Sensor Network for Flash Flood Monitoring, Diagnosis and Management in Urban Areas
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Applying query formulation and fusion techniques for cross language news story search
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In: Arora, Piyush orcid:0000-0002-4261-2860 , Foster, Jennifer orcid:0000-0002-7789-4853 and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2013) Applying query formulation and fusion techniques for cross language news story search. In: 5th Forum on Information Retrieval Evaluation (FIRE'13), 4 -6 Dec 2013, New Delhi, India. ISBN 978-1-4503- 2830-2 (2013)
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Abstract:
Cross Language News story search (CLNSS) is concerned with finding documents describing the same events in documents in different languages. As well as supporting information retrieval (IR), CLNSS has other applications in mining parallel and comparable data across different languages. In this paper, we present an overview of the work carried out for our participation in the Cross Language !ndian News Story Search (CL!NSS) task at FIRE 2013. In the CL!NSS task we explored the problem of cross language news search for the English-Hindi language pair. English news stories are used as queries to seek similar news documents from Hindi news articles. Hindi being a resource-scarce language offers many challenges towards retrieving relevant news articles. We investigate and contrast translation of input queries from English to Hindi using the Google and Bing translation services. To support translation of out-of-vocabulary words we use the Google transliteration service. A key challenge of the CL!NSS task is formation of search queries from the English news articles, since they are much longer than the much shorter queries typically used in IR applications. To address this problem, we explore the use of summarization to extract a query from the input news documents, and use these summarized queries as the input to the cross language IR system. We explore the use of query expansion using pseudo relevance feedback (PRF) in the IR process, since this has been shown to be effective for cross language IR in many previous investigations. We also explore in detail the use of data fusion techniques over different sets of retrieved results obtained using diverse query formulation techniques. For the CL!NSS task our team submitted 3 main runs. The results of our best run was ranked first among official submissions based on NDCG@5 and NDCG@10 values and second for NDCG@1 values. For the 25 test queries the results of our best main run were NDCG@1 0.7400, NDCG@5 0.6809 and NDCG@10 0.7268. We present our methodology, official results and results of a number of post-task experiments that were conducted to further examine the cross language search problem. Our experiments reveal that query formulation plays a vital role in improving search results for news documents across different languages. Instead of using the complete news documents the summarized queries show better performance. Data fusion techniques also help to improve the performance of the system by boosting the rank of documents, thus improving the NDCG scores.
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Keyword:
Computational linguistics; Cross Language News Search; Query Translation; Query Summarization; Data Fusion; Pseudo Relevance Feedback; Hindi Information Retrieval; Machine translating
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URL: http://doras.dcu.ie/22797/
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| 17 |
Combining multiple types of intelligence to generate probability maps of moving targets
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| 18 |
Employing the Intelligence Cycle Process Model Within the Homeland Security Enterprise
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In: DTIC (2013)
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Better Equipping Reserve Military Intelligence Analyst to Meet the Needs of the Commander by Championing a Process-Driven Training Model
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In: DTIC (2013)
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Combining Multiple Types of Intelligence to Generate Probability Maps of Moving Targets
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In: DTIC (2013)
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