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Using Clustering Approaches to Open-Domain Question Answering [chapter]

Youzheng Wu, Hideki Kashioka, Jun Zhao
2007 Lecture Notes in Computer Science  
The One-Sentence-Multi-Topic clustering approach is first presented, which clusters sentences to improve the language model for retrieving sentences.  ...  Second, regarding each cluster in the results for One-Sentence-Multi-Topic clustering as aligned sentences, we present a pattern-similarity-based clustering approach that automatically learns syntactic  ...  We first present a One-Sentence-Multi-Topic sentence clustering approach to the cluster-based language model to improve sentence retrieval for answering question.  ... 
doi:10.1007/978-3-540-70939-8_45 fatcat:2ivzluj64nbj7aq73e37y63lfe

Survey Paper on Generating Correlation among Different Modalities by Using Parallel Processing for Cross-Media Retrieval

Rokkam SrikanthReddy
2017 International Journal for Research in Applied Science and Engineering Technology  
In the proposed method retrieve cross-media information using multi core processer and multi-threading.  ...  The semantic level approach is the main concern to retrieving the relative information from the bag of words. Search can be based on text or other content-based information.  ...  For allow large-scale inter-media retrieval, inter-media hashing (IMH) model is a tail to cross the relation between multi media groups from different data types [1] .  ... 
doi:10.22214/ijraset.2017.8309 fatcat:5j65haeztfdedoljvqrczo2pxq

Exploiting syntactic structure of queries in a language modeling approach to IR

Munirathnam Srikanth, Rohini Srihari
2003 Proceedings of the twelfth international conference on Information and knowledge management - CIKM '03  
This paper presents a novel method for using NLP techniques on user queries, specifically, a syntactic parse of a query, in the statistical language modeling approach to IR.  ...  Natural Language Processing (NLP) techniques have been explored to enhance the performance of Information Retrieval (IR) methods with varied results.  ...  Language Modeling approach to IR, which attempts to explain the retrieval process seems to be a good framework to capture term dependencies.  ... 
doi:10.1145/956950.956952 fatcat:ssbhqrb5vvgbxir2nlrlkd3lb4

Exploiting syntactic structure of queries in a language modeling approach to IR

Munirathnam Srikanth, Rohini Srihari
2003 Proceedings of the twelfth international conference on Information and knowledge management - CIKM '03  
This paper presents a novel method for using NLP techniques on user queries, specifically, a syntactic parse of a query, in the statistical language modeling approach to IR.  ...  Natural Language Processing (NLP) techniques have been explored to enhance the performance of Information Retrieval (IR) methods with varied results.  ...  Language Modeling approach to IR, which attempts to explain the retrieval process seems to be a good framework to capture term dependencies.  ... 
doi:10.1145/956863.956952 dblp:conf/cikm/SrikanthS03 fatcat:zfiy64vbhrhrdftcvm6f4mewqq

Evaluation of a language identification system for mono- and multilingual text documents

Olga Artemenko, Thomas Mandl, Margaryta Shramko, Christa Womser-Hacker
2006 Proceedings of the 2006 ACM symposium on Applied computing - SAC '06  
Language identification is a classification task between a pre-defined model and a text in an unknown language.  ...  This paper presents the implementation of a tool for language identification for mono-and multi-lingual documents. The tool includes four algorithms for language identification.  ...  In 2005, the first multi-lingual web collection was developed for a comparative analysis of information retrieval approaches for web pages.  ... 
doi:10.1145/1141277.1141473 dblp:conf/sac/ArtemenkoMSW06 fatcat:q2ucz6kylnahlbk4jvv5jxuake

A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods [article]

Zhihan Zhang, Wenhao Yu, Mengxia Yu, Zhichun Guo, Meng Jiang
2022 arXiv   pre-print
Multi-task learning (MTL) has become increasingly popular in natural language processing (NLP) because it improves the performance of related tasks by exploiting their commonalities and differences.  ...  training and (ii) multi-step training.  ...  Retrieval-augmented generation models use the input sequence to retrieve relevant information (e.g., a background document) and use it as additional contexts when generating the target sequence.  ... 
arXiv:2204.03508v1 fatcat:xgyp3mwcc5aolgh3bsoxtov2oi

Latent concept expansion using markov random fields

Donald Metzler, W. Bruce Croft
2007 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07  
In this paper, we propose a robust query expansion technique based on the Markov random field model for information retrieval.  ...  We evaluate our technique against relevance models, a state-of-the-art language modeling query expansion technique.  ...  Acknowledgments This work was supported in part by the Center for Intelligent Information Retrieval, in part by NSF grant #CNS-0454018, in part by ARDA and NSF grant #CCF-0205575, and in part by Microsoft  ... 
doi:10.1145/1277741.1277796 dblp:conf/sigir/MetzlerC07 fatcat:zd4uzoxssje5reuvwbfc4j2jgi

A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines

Leyla Zhuhadar
2016 Figshare  
Second, term vector translation isused – a statistical multilingual text retrieval techniques that maps statistical information about termuse between languages (Ontology co-learning).  ...  In this article we illustrate a methodology for building cross-language search engine. A synergisticapproach between thesaurus-based approach and corpus-based approach is proposed.  ...  , Natural Language Processing, and multi-language information retrieval systems.  ... 
doi:10.6084/m9.figshare.3423686.v1 fatcat:h7un4wlxyfg67avecgk7ub36qu

Semantic concept-enriched dependence model for medical information retrieval

Sungbin Choi, Jinwook Choi, Sooyoung Yoo, Heechun Kim, Youngho Lee
2014 Journal of Biomedical Informatics  
In this study, we incorporate a semantic concept-based termdependence feature into a formal retrieval model to improve its ranking performance.  ...  Conclusion: By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent  ...  In a statistical language modeling approach, query q is assumed to be generated by a probabilistic model based on document d. Thus, the documents are ranked according to the query likelihood, p(q|d).  ... 
doi:10.1016/j.jbi.2013.08.013 pmid:24036003 fatcat:e2dll5bvjbbazkcggar64zwhdu

Multilingual vs. Monolingual User Models for Personalized Multilingual Information Retrieval [chapter]

M. Rami Ghorab, Séamus Lawless, Alexander O'Connor, Dong Zhou, Vincent Wade
2013 Lecture Notes in Computer Science  
This paper demonstrates that a user of multilingual search has different interests depending on the language used, and that the user model should reflect this.  ...  To demonstrate this phenomenon, the paper proposes and evaluates a set of result re-ranking algorithms based on various user model representations.  ...  English to search for technical content). Furthermore, a user may click on results of certain languages depending on the type of information sought.  ... 
doi:10.1007/978-3-642-38844-6_38 fatcat:yzencvr3srbtncllmuls3gtpem

AutoSurvey: Automatic Survey Generation based on a Research Draft

Hen-Hsen Huang
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
A neural model for information structure analysis is employed for extracting fine-grained information from the abstracts of previous work, and a novel evolutionary multi-source summarization model is proposed  ...  This work presents AutoSurvey, an intelligent system that performs literature survey and generates a summary specific to a research draft.  ...  The cross-lingual information retrieval model is a hybrid of embedding-based and term-based approaches.  ... 
doi:10.24963/ijcai.2020/761 dblp:conf/ijcai/Huang20 fatcat:rn66rm7w6vb7tofmypw6hlrelu

PSU at CLEF-2020 ARQMath Track: Unsupervised Re-ranking using Pretraining

Shaurya Rohatgi, Jian Wu, C. Lee Giles
2020 Conference and Labs of the Evaluation Forum  
For the re-ranking we use a pre-trained robertabase model (110 million parameters) to make the language model more math-aware.  ...  Our approach achieves a higher NDCG score than the baseline, while our MAP and P@10 scores are competitive, performing better than the best submission (MathDowsers) for text and text+formula dependent  ...  Special thanks to Behrooz Mansouri for providing the dataset, initial analysis of topics, and starter code to all the participants of the task; it made it easier for us to pre-process the data and jump  ... 
dblp:conf/clef/Rohatgi0G20 fatcat:76djkwmfejbeva5e7j2y74irve

Dynamic language modeling for a daily broadcast news transcription system

Ciro Martins, Antonio Teixeira, Joao Neto
2007 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)  
Using an Information Retrieval engine, relevant documents are extracted from a large corpus to generate a story-based LM.  ...  To address this problem, we propose a daily and unsupervised adaptation approach which dynamically adapts the active vocabulary and LM to the topic of the current news segment during a multi-pass speech  ...  Ciro Martins is sponsored by a FCT scholarship (SFRH/BD/23360/2005).  ... 
doi:10.1109/asru.2007.4430103 dblp:conf/asru/MartinsTN07 fatcat:75ckqwyvqvaafceasqmywvmnhi

Efficient Search Mechanism from Large Scale Corpora for Domain-Specific Language Modeling in Speech Recognition

2019 International Journal of Engineering and Advanced Technology  
A word level and a phrase level retrieval process for creating domain-specific language model has been implemented.  ...  This assisted us in tuning the language model in accordance with the domain and also by reducing the search time by more than 90% in comparison to conventional search and retrieval mechanism used in our  ...  Training of context dependent multi-state HMM models comprises of training Context Independent HMM models, Context Dependent HMM models, building decision trees and Gaussian mixture generation.  ... 
doi:10.35940/ijeat.f8416.088619 fatcat:xvkfevoszjeydioplntpvca6d4

Fielded Sequential Dependence Model for Ad-Hoc Entity Retrieval in the Web of Data

Nikita Zhiltsov, Alexander Kotov, Fedor Nikolaev
2015 Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '15  
Previously proposed approaches to ad-hoc entity retrieval in the Web of Data (ERWD) used multi-fielded representation of entities and relied on standard unigram bag-of-words retrieval models.  ...  In this work, we propose a novel retrieval model that incorporates term dependencies into structured document retrieval and apply it to the task of ERWD.  ...  Acknowledgments This work was partially supported by the subsidy from the government of the Russian Federation to support the program of competitive growth of Kazan Federal University among world class  ... 
doi:10.1145/2766462.2767756 dblp:conf/sigir/ZhiltsovKN15 fatcat:3t3kx4wb5rdhxigcffp3jger5q
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