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Dataset search: a survey

Adriane Chapman, Elena Simperl, Laura Koesten, George Konstantinidis, Luis-Daniel Ibáñez, Emilia Kacprzak, Paul Groth
2019 The VLDB journal  
Here, we survey the state of the art of research and commercial systems and discuss what makes dataset search a field in its own right, with unique challenges and open questions.  ...  These developments foreshadow an emerging research field around dataset search or retrieval that broadly encompasses frameworks, methods and tools that help match a user data need against a collection  ...  Acknowledgements The following projects supported this work: They-BuyForYou (EU H2020: 780247); Data Stories (EPRSC: EP/P025676/1); QROWD (EU:H2020 732194); A Multidisciplinary Study of Predictive Artificial  ... 
doi:10.1007/s00778-019-00564-x fatcat:tmjhtnkzsfedzhqxeyxifoteli

Dataset search: a survey [article]

Adriane Chapman and Elena Simperl and Laura Koesten and George Konstantinidis and Luis-Daniel Ibáñez-Gonzalez and Emilia Kacprzak and Paul Groth
2019 arXiv   pre-print
Here, we survey the state of the art of research and commercial systems in dataset retrieval.  ...  We identify what makes dataset search a research field in its own right, with unique challenges and methods and highlight open problems.  ...  Current commercial dataset search offerings are outlined in Section 3 while Section 4 provides a survey of dataset search research.  ... 
arXiv:1901.00735v1 fatcat:lvz3zfkpejfqdmdxmi2lswn45y

A Survey: Searching Techniques

Miss Mangala S. Teli, Asst. Prof. Priti S. Subramanium
2017 IOSR Journal of Computer Engineering  
Any user who doesn't know how to search can get result by simply typing related words in search engine.  ...  In day to day life as we are using internet mostly for to search every one want answer within short time.  ...  The multiple experiments are carried out over very large textA Survey: Searching Techniques DOI: 10.9790/0661-1903064748  ... 
doi:10.9790/0661-1903064748 fatcat:dki5qs5n6fa4jee6edkgoivkvy

Survey on Nearest Keyword Set Search in Multi-dimensional Datasets

A. Jebamalar, Anbuselvi Anbuselvi
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Keyword query in multi-dimensional datasets is a noteworthy application in information mining.  ...  This propels us to study a non-particular version of Closest Keywords search called Best Keyword Cover which considers among items remove and also the watchword evaluation of articles.  ...  Our observational assessments on genuine and engineered datasets show the adequacy of our procedures. To the best of our insight, this is the lay work on location aware type-ahead search.  ... 
doi:10.23956/ijarcsse.v7i8.23 fatcat:v7ftwdrhjjalbarnbbq6bwg5be

Evolution of biosequence search algorithms: a brief survey [article]

Gregory Kucherov
2018 arXiv   pre-print
The paper surveys the evolution of main algorithmic techniques to compare and search biological sequences.  ...  We further emphasize recently emerged and growing applications of sketching methods which support comparison of massive datasets, such as metagenomics samples.  ...  Besides dealing with very large datasets, MinHashing provides a way to improve seed-based sequence search (cf above) by using minimizers as seeds.  ... 
arXiv:1808.01038v4 fatcat:uiyjrwvgprgu3nfcu6i47o4wpe

Graph neural architecture search: A survey

Babatounde Moctard Oloulade, Jianliang Gao, Jiamin Chen, Tengfei Lyu, Raeed Al-Sabri
2022 Tsinghua Science and Technology  
Hence, many studies have focused on building automated machine learning frameworks to search for the best GNN models for targeted tasks.  ...  In this work, we provide a comprehensive review of automatic GNN model building frameworks to summarize the status of the field to facilitate future progress.  ...  Differences with existing surveys. The studies involving Graph-NAS surveys are limited. Xie et al. [19] provided an exhaustive enumeration of optimization strategies in neural architecture search.  ... 
doi:10.26599/tst.2021.9010057 fatcat:f4dck2qxjfbgbjc6h5u6ptw4ny

A Survey on Neural Architecture Search [article]

Martin Wistuba and Ambrish Rawat and Tejaswini Pedapati
2019 arXiv   pre-print
With this survey, we provide a formalism which unifies and categorizes the landscape of existing methods along with a detailed analysis that compares and contrasts the different approaches.  ...  The growing interest in both the automation of machine learning and deep learning has inevitably led to the development of a wide variety of automated methods for neural architecture search.  ...  In the rest of this survey, we use search space to refer to the set of feasible solutions of a neural architecture search method.  ... 
arXiv:1905.01392v2 fatcat:px7iiwwdjzamfhecynvafcimqu

Search Facets and Ranking in Geospatial Dataset Search

Thomas Hervey, Sara Lafia, Werner Kuhn, Judith A. Verstegen, Krzysztof Janowicz
2020 International Conference Geographic Information Science  
This study surveys the state of search on open geospatial data portals.  ...  We find that most users initiate a search using a text input and several pre-created facets (such as a filter for tags or format). Some portals supply a map-view of data or topic explorers.  ...  We surveyed the front end of systems and focused on search facets, a type of control users have while searching.  ... 
doi:10.4230/lipics.giscience.2021.i.5 dblp:conf/giscience/HerveyLK21 fatcat:2fnxysem55dd7lzfdukv6d5bgy

A Survey on Evolutionary Neural Architecture Search [article]

Yuqiao Liu, Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, Kay Chen Tan
2021 arXiv   pre-print
Neural Architecture Search (NAS) is a type of technology that can design the architectures automatically.  ...  Unfortunately, there has not yet been a comprehensive summary of the EC-based NAS algorithms.  ...  AA (1) where A denotes the search space of the neural architectures, L(·) measures the performance of the architecture A on the validation dataset D valid after being trained on the training dataset  ... 
arXiv:2008.10937v3 fatcat:tqk5trje4rg2zp443ndjvlpzfu

Hashing for Similarity Search: A Survey [article]

Jingdong Wang, Heng Tao Shen, Jingkuan Song, Jianqiu Ji
2014 arXiv   pre-print
Similarity search (nearest neighbor search) is a problem of pursuing the data items whose distances to a query item are the smallest from a large database.  ...  In this paper, we present a survey on one of the main solutions, hashing, which has been widely studied since the pioneering work locality sensitive hashing.  ...  Finally, Section 9 concludes this survey.  ... 
arXiv:1408.2927v1 fatcat:reknwesjnbafvcbouyudrzp4rq

String similarity search and join: a survey

Minghe Yu, Guoliang Li, Dong Deng, Jianhua Feng
2015 Frontiers of Computer Science  
Although these two problems have been extensively studied in decade, there is no thorough survey. In this paper, we present a comprehensive survey on string similarity search and join.  ...  Finally, we provide some open datasets and summarize some research challenges and open problems.  ...  They also provided with many open datasets and experimental results. Conclusion and Open Problems In this paper we provide a comprehensive survey on string similarity search and join.  ... 
doi:10.1007/s11704-015-5900-5 fatcat:n6j4xqojhjgulmzblhbygjuqs4

A Survey on Nearest Neighbor Search Methods

Mohammad RezaAbbasifard, Bijan Ghahremani, Hassan Naderi
2014 International Journal of Computer Applications  
This definition for a small dataset with low dimension has sub linear (or even logarithmic) query time, but for massive dataset with high dimension is exponential [2] .  ...  Among the others, nearest neighbor search is one of the best techniques to this end which is focused by many researchers. Different techniques are used for nearest neighbor search.  ...  A naive solution for the NNS problem is using linear search method that computes distance from the query to every single point in the dataset and returns the k closest points.  ... 
doi:10.5120/16754-7073 fatcat:465jmoyauzabrle4u62l6xld5a

A survey on search results diversification techniques

Adnan Abid, Naveed Hussain, Kamran Abid, Farooq Ahmad, Muhammad Shoaib Farooq, Uzma Farooq, Sher Afzal Khan, Yaser Daanial Khan, Muhammad Azhar Naeem, Nabeel Sabir
2015 Neural computing & applications (Print)  
Our system firstly selects a feature selection model for designing an effective XML keyword search from a large database. Then it will automatically diversify the keyword search.  ...  For searching keyword from XML data a short and vague keyword query is used. Feature selection model is used to derive search candidate of the query search.  ...  Literature Survey: Search the result of diversification can be achieved by the relevance of query and documents and similarity between documents in the set of result.  ... 
doi:10.1007/s00521-015-1945-5 fatcat:a2hd7x4kcfhktimz4p2ascnvpq

A Survey on Set Similarity Search and Join

Lianyin Jia
2018 International Journal of Performability Engineering  
To bridge this gap, this paper provides a comprehensive survey of set similarity search and join.  ...  The survey starts from the basic definitions, framework, ordering and similarity functions of set similarity search and join.  ...  For example, in e-commerce sites, we need to query which users buy beer and diapers together (a subset search), and which users have similar shopping habits (a similarity search).  ... 
doi:10.23940/ijpe.18.02.p6.245258 fatcat:3uhb3ngnyfbxnnnthxnlfcs7re

Facial Image Classification And Searching –A Survey

Vijayarani S, Vinupriya M
2014 International Journal of Information Technology, Modeling and Computing  
Though tracking and recognizing face objects is a routine task, building such a system is still an active research.  ...  Also, this paper provides a marginal summary for future research and enhancements in face detection.  ...  Section 3 discusses about the importance of classification and searching in facial images. Section 4 provides a literature survey.  ... 
doi:10.5121/ijitmc.2014.2203 fatcat:xaovrnj45zhgnk5wkglpgqrv4a
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