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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Promoting user engagement and learning in search tasks by effective document representation Arora, Piyush. - : Dublin City University. School of Computing, 2018. : Dublin City University. ADAPT, 2018 In: Arora, Piyush orcid:0000-0002-4261-2860 (2018) Promoting user engagement and learning in search tasks by effective document representation. PhD thesis, Dublin City University. (2018) BASE Show details 2 How do users perceive information: analyzing user feedback while annotating textual units Jones, Gareth J.F.; Arora, Piyush In: Arora, Piyush orcid:0000-0003-0055-345X and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2017) How do users perceive information: analyzing user feedback while annotating textual units. In: CHIIR 2017 Workshop on Supporting Complex Search Tasks, 11 Mar 2017, Oslo, Norway. (2017) BASE Show details 3 DCU-SEManiacs at SemEval-2016 task 1: synthetic paragram embeddings for semantic textual similarity Hokamp, Chris; Arora, Piyush In: Hokamp, Chris orcid:0000-0002-7850-9398 and Arora, Piyush orcid:0000-0002-4261-2860 (2016) DCU-SEManiacs at SemEval-2016 task 1: synthetic paragram embeddings for semantic textual similarity. In: 10th International Workshop on Semantic Evaluation (SemEval-2016), 16-17 June 2016, San Diego, Ca. USA. (2016) BASE Show details 4 A comparative study of online translation services for cross language Information retrieval Liu, Qun; Jones, Gareth J.F.; Arora, Piyush... In: Hosseinzadeh Vahid, Ali, Arora, Piyush orcid:0000-0002-4261-2860 , Liu, Qun orcid:0000-0002-7000-1792 and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2015) A comparative study of online translation services for cross language Information retrieval. In: 24th International Conference on World Wide Web Companion, 18–22 May 2015, Florence, Italy. ISBN 978-1-4503-3473-0 (2015) BASE Show details 5 DCU: using distributional semantics and domain adaptation for the semantic textual similarity SemEval-2015 Task 2 Foster, Jennifer; Hokamp, Chris; Jones, Gareth J.F.... In: Arora, Piyush orcid:0000-0002-4261-2860 , Hokamp, Chris orcid:0000-0002-7850-9398 , Foster, Jennifer orcid:0000-0002-7789-4853 and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2015) DCU: using distributional semantics and domain adaptation for the semantic textual similarity SemEval-2015 Task 2. In: International Workshop on Semantic Evaluation (SemEval 2015), 4-5 June 2015, Denver, Co. USA. (2015) BASE Show details 6 DCU: aspect-based polarity classification for SemEval task 4 Wagner, Joachim; Foster, Jennifer; Arora, Piyush... In: Wagner, Joachim orcid:0000-0002-8290-3849 , Arora, Piyush orcid:0000-0002-4261-2860 , Cortes, Santiago, Barman, Utsab, Bogdanova, Dasha, Foster, Jennifer orcid:0000-0002-7789-4853 and Tounsi, Lamia (2014) DCU: aspect-based polarity classification for SemEval task 4. In: International Workshop on Semantic Evaluation (SemEval-2014), 23-24 Aug 2014, Dublin, Ireland. ISBN 978-1-941643-24-2 (2014) BASE Show details 7 DCU at FIRE 2013: cross-language !ndian news story search Foster, Jennifer; Jones, Gareth J.F.; Arora, Piyush 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) DCU at FIRE 2013: cross-language !ndian news story search. In: FIRE-Forum for Information Retrieval Evaluation, 5-7 Dec 2013, Bangalore, India. (2013) BASE Show details 8 Applying query formulation and fusion techniques for cross language news story search Arora, Piyush; Jones, Gareth J.F.; Foster, Jennifer 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) 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. Keyword: Computational linguistics; Cross Language News Search; Query Translation; Query Summarization; Data Fusion; Pseudo Relevance Feedback; Hindi Information Retrieval; Machine translating URL: http://doras.dcu.ie/22797/ BASE Hide details

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