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Word Embedding based Approaches for Information Retrieval

Dwaipayan Roy
2017 BCS-IRSG Symposium on Future Directions in Information Access  
In this paper, some of the approaches that use word embedding for better retrieval is presented.  ...  Word Embedding based Relevance Model (Roy et al. 2016a) As shown in Section 3.1 that simple approaches using word embedding for retrieval can results in significantly better performance.  ... 
doi:10.14236/ewic/fdia2017.9 dblp:conf/fdia/Roy17 fatcat:m6ga4t5hgbaltpayi3hoodm2ia

Exploring Summary-Expanded Entity Embeddings for Entity Retrieval

Shahrzad Naseri, John Foley, James Allan, Brendan T. O'Connor
2018 International Conference on Information and Knowledge Management  
Word and entity embeddings are a promising opportunity for new improvements in retrieval, especially in the presence of vocabulary mismatch problems.  ...  Entity retrieval is an important part of any modern retrieval system and often satisfies user information needs directly.  ...  Acknowledgement This work was supported in part by the Center for Intelligent Information Retrieval and in part by NSF grant #IIS-1617408.  ... 
dblp:conf/cikm/NaseriFAO18 fatcat:jzy5cgrjbrfbzfprhis2vni74q

BERT-Based Embedding Model for Formula Retrieval

Pankaj Dadure, Partha Pakray, Sivaji Bandyopadhyay
2021 Conference and Labs of the Evaluation Forum  
In this paper, we have presented the BERT-based formula embedding model to facilitated formula retrieval in ARQMath2 tasks.  ...  The obtained results have shown that the proposed approach provides better fits than existing embedding approaches and infers the meaningful semantic relationships between equations.  ...  for providing infrastructural facilities and support.  ... 
dblp:conf/clef/DadurePB21 fatcat:qsbvf2gqxjbfhpek7m77m2zuve

AUTOMATIC CV RANKING USING DOCUMENT VECTOR AND WORD EMBEDDING

Ansa Abdul Noor, Maheen Bakhtyar, Bilal Ahmed Chandio, Rehana Gull, Junaid Baber
2021 Zenodo  
The primary purpose of this research study is to exploit the class NLP techniques to perform the information retrieval task for resume ranking based on job description similarity.  ...  In this proposed methodology, we compared document vectors with word embedding. Experiments show that word embedding method is more effective than the document vector.2  ...  In this research, two famous approaches of information retrieval are evaluated for CV ranking. The word embedding-based approach is more effective than the document vector-based approach.  ... 
doi:10.5281/zenodo.5089433 fatcat:dx4tljt6wzalfor2ouoi7wbuw4

3D Model Retrieval based on a 3D Shape Knowledge Graph

Weizhi Nie, Ya Wang, Dan Song, Wenhui Li
2020 IEEE Access  
Our approach focuses on the structural information of 3D model and is not restricted by the database. We evaluate the proposed method on the ModelNet40 dataset for the 3D model retrieval task.  ...  Second, we construct a 3D shape knowledge graph based on the geometric words, models and their relations. Additionally, we propose a novel graph embedding method to generate embeddings of nodes.  ...  A more recent trend for entity-based retrieval models is to firstly build the representation for entity-based text and then improve the word-based ranking. Hasibi et al.  ... 
doi:10.1109/access.2020.3013595 fatcat:dao3eghhyjarpnv2lujfkvjxm4

A Hybrid Embedding Approach to Noisy Answer Passage Retrieval [chapter]

Daniel Cohen, W. Bruce Croft
2018 Lecture Notes in Computer Science  
over a word based approach as the collections degrade in quality.  ...  In this paper, we demonstrate the flexibility of a character based approach on the task of answer passage retrieval, agnostic to the source of embeddings and with improved performance in P@1 and MRR metrics  ...  Acknowledgments This work was supported in part by the Center for Intelligent Information Retrieval, in part by NSF IIS-1160894 and in part by NSF grant #IIS-1419693.  ... 
doi:10.1007/978-3-319-76941-7_10 fatcat:6glb3eh65rg3ng5rfatuz5edim

Comparison of Several Word embedding Sources for Medical Information Retrieval

Julie Budaher, Mohannad Almasri, Lorraine Goeuriot
2016 Conference and Labs of the Evaluation Forum  
The aim of this task is to evaluate the effectiveness of information retrieval systems when searching for health content on the web.  ...  Our submission investigates the effectiveness of word embedding for query expansion in the health domain. We experiment two variants of query expansion method using word embedding.  ...  Is the word embedding approach for query expansion effective for consumer health search? 2. What influence has the word embedding source on the results? This paper is organized as follows.  ... 
dblp:conf/clef/BudaherAG16 fatcat:tfbe3euakzb73mq27kwmudjnzu

A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases [article]

Tolgahan Cakaloglu, Xiaowei Xu
2019 arXiv   pre-print
To this end, we first compare the quality of various text-embedding methods for retrieval performance and give an extensive empirical comparison with the performance of various non-augmented base embeddings  ...  Deep language models learning a hierarchical representation proved to be a powerful tool for natural language processing, text mining and information retrieval.  ...  as the representation for information retrieval.  ... 
arXiv:1902.00663v7 fatcat:br6tdbqei5eudca2tsq3crrexq

Query Expansion for Sentence Retrieval Using Pseudo Relevance Feedback and Word Embedding [chapter]

Piyush Arora, Jennifer Foster, Gareth J. F. Jones
2017 Lecture Notes in Computer Science  
Two alternative QE approaches: i) pseudo relevance feedback (PRF), using Robertson term selection, and ii) word embeddings (WE) of query words, are explored.  ...  This study investigates the use of query expansion (QE) methods in sentence retrieval for non-factoid queries to address the query-document term mismatch problem.  ...  We thank the reviewers for their feedback and comments. This research is supported by Science Foundation Ireland (SFI) as a part of the ADAPT Centre at Dublin City University (Grant No: 12/CE/I2267).  ... 
doi:10.1007/978-3-319-65813-1_8 fatcat:2cddt2e6gvdqxit3ehltyrtyqu

RelEmb: A relevance-based application embedding for Mobile App retrieval and categorization [article]

Ahsaas Bajaj, Shubham Krishna, Mukund Rungta, Hemant Tiwari, Vanraj Vala
2019 arXiv   pre-print
Information Retrieval Systems have revolutionized the organization and extraction of Information.  ...  Usage of app-embedding for query expansion, nearest neighbor analysis enables unique and interesting use cases to enhance end-user experience with mobile apps.  ...  For the domain of information retrieval, it can be said that a word is known by the documents (or other words) it retrieves.  ... 
arXiv:1904.06672v1 fatcat:ivipglhnpjcqvakd56aysrvlly

Using Word Embeddings for Query Translation for Hindi to English Cross Language Information Retrieval

Paheli Bhattacharya, Pawan Goyal, Sudeshna Sarkar
2016 Journal of Computacion y Sistemas  
The proposed word embedding based approach outperforms the basic dictionary based approach by 70% and when the word embeddings are combined with the dictionary, the hybrid approach beats the baseline dictionary  ...  We experiment with Forum for Information Retrieval and Evaluation (FIRE) 2008 and 2012 datasets for Hindi to English CLIR.  ...  Acknowledgments We would like to thank the anonymous reviewers for their valuable comments.  ... 
doi:10.13053/cys-20-3-2462 fatcat:zs44l332ivd77gglzixrnde3ay

Learning supervised embeddings for large scale sequence comparisons [article]

Dhananjay Kimothi, Pravesh Biyani, James M Hogan, Akshay Soni, Wayne Kelly
2019 bioRxiv   pre-print
Our method extends earlier Representation Learning (RL) based methods to include jointly contextual and class-related information for each sequence during training.  ...  The SuperVec approach is extended further through H-SuperVec, a tree-based hierarchical method which learns embeddings across a range of feature spaces based on the class labels and their exclusive and  ...  Follow up works [16] [17] [18] extended the idea of word embedding to learning of embeddings for the whole document, based on suitable combinations of word embeddings. Asgari et. al.  ... 
doi:10.1101/620153 fatcat:awhslcijwjaolmv5e6dxsrknoi

Enhancing Information Retrieval with Adapted Word Embedding

Navid Rekabsaz
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
Recent developments on word embedding provide a novel source of information for term-to-term similarity.  ...  In this paper, we propose addressing the question of combining the term-to-term similarity of word embedding with IR models. The retrieval models in the  ...  As the basis of our approach, we consider the terms as concepts and define the relation between them based on the term-term similarity of word embedding models.  ... 
doi:10.1145/2911451.2911475 dblp:conf/sigir/Rekabsaz16 fatcat:hvsac5ib7zgdxbasxqjfqxg46y

Enhancing Cross-modal Retrieval Based on Modality-specific and Embedding Spaces

Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama
2020 IEEE Access  
However, we argue that the forced embedding optimization results in loss of key information for sentences and images.  ...  Most of the existing methods learn optimal embeddings of visual and lingual information to a single common representation space.  ...  approach is effective for various conventional embedding methods to improve the retrieval performance of vision and language retrieval.  ... 
doi:10.1109/access.2020.2995815 fatcat:ar7zdjypivfdrmakffvilmhdfy

Integrating and Evaluating Neural Word Embeddings in Information Retrieval

Guido Zuccon, Bevan Koopman, Peter Bruza, Leif Azzopardi
2015 Proceedings of the 20th Australasian Document Computing Symposium on ZZZ - ADCS '15  
To this aim, we use neural word embeddings within the well known translation language model for information retrieval.  ...  Despite these promising results, there has been little analysis of the use of these word embeddings for retrieval.  ...  TRANSLATION LANGUAGE MODELS FOR INFORMATION RETRIEVAL Statistical Translation Language Models The use of language modelling for information retrieval is an attractive approach as it directly models how  ... 
doi:10.1145/2838931.2838936 dblp:conf/adcs/ZucconKBA15 fatcat:2z6gtv42t5f57chcojzjio3yde
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