Filters








97,102 Hits in 5.4 sec

Probabilistic Topic Models for Learning Terminological Ontologies

Wei Wang, Payam Mamaani Barnaghi, Andrzej Bargiela
2010 IEEE Transactions on Knowledge and Data Engineering  
Extraction, and Natural Language Processing.  ...  In the past few years, researchers from various areas such as Information Retrieval, Database, Natural Language Processing, Knowledge Management, and Machine Learning started speculating on the possibility  ... 
doi:10.1109/tkde.2009.122 fatcat:ckvvtgj5ybg7ngwk3y7x5ysjta

Expert Finding in Heterogeneous Bibliographic Networks with Locally-trained Embeddings [article]

Huan Gui, Qi Zhu, Liyuan Liu, Aston Zhang, Jiawei Han
2018 arXiv   pre-print
Expert finding is an important task in both industry and academia. It is challenging to rank candidates with appropriate expertise for various queries.  ...  information for specific queries.  ...  Meanwhile, "information extraction" is close to both "natural language processing" and "named entity recognition".  ... 
arXiv:1803.03370v1 fatcat:sonvdldbkjaxzlckigevhmsaeq

An Introduction to Neural Information Retrieval t

Bhaskar Mitra, Nick Craswell
2018 Foundations and Trends in Information Retrieval  
Ma, and H. Li. 2009. "Ranking measures and loss functions in learning to rank". In: Advances in Neural Information Processing Systems. 315-323. Chen, W., D. Grangier, and M. Auli. 2015b.  ...  In general, many natural language processing tasks do not involve information access and retrieval, so are not IR tasks, but some can still be useful as part of a larger IR system.  ... 
doi:10.1561/1500000061 fatcat:3fwzyu7lrbavtdllirjaiugp7y

Information Retrieval with Verbose Queries

Manish Gupta, Michael Bendersky
2015 Foundations and Trends in Information Retrieval  
The current plan is to divide the tutorial into two main parts, each focusing on applications of the discussed techniques to verbose natural language queries.  ...  Pre-requisites: Introductory-level knowledge in information retrieval, query log mining, web mining, algorithms, natural language processing and machine learning.  ...  -Unsupervised Segmentation using Generative Language Models and Wikipedia [38] . • Query-Dependent Learning-to-Rank -Query-Dependent Ranking Models [17] . -Two-Stage Learning-to-Rank Models [14] .  ... 
doi:10.1561/1500000050 fatcat:nh36avhvtnezpokjvjytzoqely

A Survey of Designing Multilingual Document Retrieval and Ranking in Cloud

Manju More E
2019 International Journal for Research in Applied Science and Engineering Technology  
to the query irrespective of query's language is ranking for multilingual information retrieval (MLIR).  ...  MLIR plays and involves the task of Cross Lingual Information Retrieval for each different desired languages.  ...  Feature Engineering In case of Information Retrieval and Natural Language Processing, it is a process of answering a question in a natural language.  ... 
doi:10.22214/ijraset.2019.7154 fatcat:jk76t7r5zngcrawe5u7gzmdbtu

Towards Understanding Theoretical Developments in Natural Language Processing

Mehnaz khan, Dr. Mehraj-ud-Din Dar, Dr. S.M.K. Quadri
2012 International Journal of Computer Applications  
We also discuss automatic abstracting and information retrieval in natural language processing applications.  ...  They use these details to develop the tools for making the computers understand and manipulate the natural languages to perform the desired tasks.  ...  Natural Language Processing is a field of AI that consists of analyzing how computers can be used to understand and manipulate natural language text or speech to do useful things.  ... 
doi:10.5120/4577-6749 fatcat:ywt5dem6qnc6bg2lbcqdxcryva

Applications and Future of Dense Retrieval in Industry

Yubin Kim
2022 Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval  
His research area is in the intersection of information retrieval, natural language processing, and deep learning.  ...  He holds a Ph.D. from New York Uni- versity (NYU), where he worked on the intersection of Deep Learning, Natural Language Processing, and Information Retrieval under the supervision of prof.  ... 
doi:10.1145/3477495.3536324 fatcat:riyl7f3rmjbjzcnfucrcbexrmu

AN AUTOMATIC WEB-BASED QUESTION ANSWERING SYSTEM FOR E-LEARNING

Waheeb Ahmed, Babu Anto
2017 Ìnformacìjnì Tehnologì ì Zasobi Navčannâ  
Several approaches employ natural language processing technology to understand questions given in natural language text, which is incomplete and error-prone.  ...  An automatic web based Question Answering (QA) system is a valuable tool for improving e-learning and education.  ...  This paper proposes a learning support system to answer questions given in natural language aided by a set of Natural Language Processing technologies.  ... 
doi:10.33407/itlt.v58i2.1567 fatcat:ajwsxxvubberfbdmfihxoeqdai

Knowledge retrieval for scientific literatures

Chun Guo, Renuka Chinchankar, Xiaozhong Liu
2012 Proceedings of the American Society for Information Science and Technology  
The system benefits users by providing structure-level access to scientific papers and automatically inferring structural knowledge from their natural language queries by leveraging knowledge recommendation  ...  In this paper, we propose innovative and economical ways to generate knowledge-based structural metadata and demonstrate a prototype knowledge retrieval system, WikiBackyard, to serve user's knowledge  ...  from users' natural language queries to better aid their retrieval process.  ... 
doi:10.1002/meet.14504901152 fatcat:ld3kmtsv7bbjzae5wit7ed4v6m

Rethinking Search: Making Experts out of Dilettantes [article]

Donald Metzler, Yi Tay, Dara Bahri, Marc Najork
2021 arXiv   pre-print
This paper examines how ideas from classical information retrieval and large pre-trained language models can be synthesized and evolved into systems that truly deliver on the promise of expert advice.  ...  When experiencing an information need, users want to engage with an expert, but often turn to an information retrieval system, such as a search engine, instead.  ...  Learning to Rank for Information Retrieval.  ... 
arXiv:2105.02274v1 fatcat:qdghlnv2nnfhnoo6eafdaxqxzy

An approach based on Combination of Features for automatic news retrieval [article]

Mohammad Moradi, Elham Ghanbari, Mehrdad Maeen, Sasan Harifi
2020 arXiv   pre-print
Content providers now need a precise and efficient way to retrieve news with the least human help. Data mining has led to the emergence of new methods for detecting related and unrelated documents.  ...  The internet has become one of the main sources of information for users and their favorite topics. It also provides access to more information.  ...  Information Extraction (IE) is a sub-area of natural language processing.  ... 
arXiv:2004.11699v1 fatcat:vppybnsh4rdixiqz3vrdsf2iva

Online Learning to Rank for Cross-Language Information Retrieval

Razieh Rahimi, Azadeh Shakery
2017 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '17  
CCS CONCEPTS •Information systems →Users and interactive retrieval; Learning to rank; Multilingual and cross-lingual retrieval; KEYWORDS Online learning; Learning to rank; Cross-language information retrieval  ...  Online learning to rank for information retrieval has shown great promise in optimization of Web search results based on user interactions.  ...  ACKNOWLEDGMENTS is research was in part supported by a grant from the Institute for Research in Fundamental Sciences (No. CS1396-4-51).  ... 
doi:10.1145/3077136.3080710 dblp:conf/sigir/RahimiS17 fatcat:rxujxfnszvh2thabwe5yln7n4i

Creating Information-maximizing Natural Language Messages Through Image Captioning-Retrieval

Fabian Karl, Mikko Lauri, Chris Biemann
2019 Conference on Natural Language Processing  
The main goal is to be able to generate information-maximizing natural language messages.  ...  To solve the ICR problem, we design and implement an end-to-end neural network architecture that describes the content of images in natural language, and retrieves them solely based on these generated  ...  The learning rate is set to 0.0002 for the first 20 epochs and then decreased to 0.00002 for the rest of the training process.  ... 
dblp:conf/konvens/KarlLB19 fatcat:my6kl6gkungvdefqwnhjnvzcz4

Taking Advantage of LOM Semantics for Supporting Lesson Authoring [chapter]

Olivier Motelet, Nelson A. Baloian
2005 Lecture Notes in Computer Science  
Nevertheless, few work was done on taking advantage of LOMsemantics to facilitate retrieval of learning material.  ...  Learning Object Metadata (LOM) is an interoperable standard focused on enabling the reuse of learning material for authoring lessons.  ...  Semantic-based Query and Ranking Data Generator The generator component is intended to provide semantic-based queries to the query processing component and also ranking information to the result processing  ... 
doi:10.1007/11575863_139 fatcat:jtudbm7yffapzfufxatp3e4k6y

Resource description framework triples entity formations using statistical language model

R.A. Kadir, R.A. Yauri
2018 Journal of Fundamental and Applied Sciences  
A method for RDF entity formations from a paragraph of text using statistical language model based on N implementation of RDF entity formation is applied on natural language query for information retrieval  ...  The DF entity formation is applied on natural language query for information retrieval of the Islamic knowledge. 300 concepts from the English translation of Holy Quran with 350 relationships are used  ...  Due to the ultimate usage of semantic web in helping users to locate, organize and process the information, there is no doubt that information is accessed or retrieved by human in a most comfortable language  ... 
doi:10.4314/jfas.v9i4s.40 fatcat:tov4yny6i5dctj5qfltymhehxm
« Previous Showing results 1 — 15 out of 97,102 results