Relevant bibliographies by topics / Keyword-based search

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Keyword-based search'

Author: Grafiati
Published: 10 January 2023
Last updated: 28 January 2023

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Journal articles on the topic "Keyword-based search"

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Kurhekar, Miss Rachana V., and Prof R. R. Shelke. "Location Based Nearest Keyword Search." International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (December 31, 2017): 1617–23. http://dx.doi.org/10.31142/ijtsrd8296.

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Seethalakshmi, G., and J. Swathi. "XML based Keyword Search." International Journal of Computer Applications 107, no. 15 (December 18, 2014): 1–3. http://dx.doi.org/10.5120/18824-0241.

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Yang Chen, Yang Chen, Yang Liu Yang Chen, Jin Pan Yang Liu, Fei Gao Jin Pan, and Emmanouil Panaousis Fei Gao. "Privacy-Protecting Attribute-Based Conjunctive Keyword Search Scheme in Cloud Storage." 網際網路技術學刊 24, no. 1 (January 2023): 065–75. http://dx.doi.org/10.53106/160792642023012401007.

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<p>Cloud storage has been deployed in various real-world applications. But how to enable Internet users to search over encrypted data and to enable data owners to perform fine-grained search authorization are of huge challenge. Attribute-based keyword search (ABKS) is a well-studied solution to the challenge, but there are some drawbacks that prevent its practical adoption in cloud storage context. First, the access policy in the index and the attribute set in the trapdoor are both in plaintext, they are likely to reveal the privacy of data owners and users. Second, the current ABKS schemes cannot provide multi-keyword search under the premise of ensuring security and efficiency. We explore an efficient way to connect the inner product encryption with the access control mechanism and search process in ABKS, and propose a privacy-protecting attribute-based conjunctive keyword search scheme. The proposed scheme provides conjunctive keyword search and ensures that the access policy and attribute set are both fully hidden. Formal security models are defined and the scheme is proved IND-CKA, IND-OKGA, access policy hiding and attribute set hiding. Finally, empirical simulations are carried out on real-world dataset, and the results demonstrate that our design outperforms other existing schemes in security and efficiency.</p> <p>&nbsp;</p>
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Hristidis, Vagelis, Heasoo Hwang, and Yannis Papakonstantinou. "Authority-based keyword search in databases." ACM Transactions on Database Systems 33, no. 1 (March 2008): 1–40. http://dx.doi.org/10.1145/1331904.1331905.

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Murali, Pranav. "An Approach to Trie Based Keyword Search for Search Engines." International Journal of Library and Information Services 6, no. 1 (January 2017): 1–16. http://dx.doi.org/10.4018/ijlis.2017010101.

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Search Engines use indexing techniques to minimize the time taken to find the relevant information to a search query. They maintain a keywords list that may reside either in the memory or in the external storage, like a hard disk. While a pure binary search can be used for this purpose, it suffers from performance issue when keywords are stored in the external storage. Some implementations of search engines use a B-tree and sparse indexes to reduce access time. This paper aims at reducing the keyword access time further. It presents a keyword search technique that utilizes a combination of trie data structure and a new keyword prefixing method. Experimental results show good improvement in performance over pure binary search. The merits of incorporating trie based approach into contemporary indexing methods is also discussed. Keyword prefixing method is described and some salient steps in the process of keyword generation are outlined.
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Bou, Savong, Toshiyuki Amagasa, and Hiroyuki Kitagawa. "Path-based keyword search over XML streams." International Journal of Web Information Systems 11, no. 3 (August 17, 2015): 347–69. http://dx.doi.org/10.1108/ijwis-04-2015-0013.

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Purpose – In purpose of this paper is to propose a novel scheme to process XPath-based keyword search over Extensible Markup Language (XML) streams, where one can specify query keywords and XPath-based filtering conditions at the same time. Experimental results prove that our proposed scheme can efficiently and practically process XPath-based keyword search over XML streams. Design/methodology/approach – To allow XPath-based keyword search over XML streams, it was attempted to integrate YFilter (Diao et al., 2003) with CKStream (Hummel et al., 2011). More precisely, the nondeterministic finite automation (NFA) of YFilter is extended so that keyword matching at text nodes is supported. Next, the stack data structure is modified by integrating set of NFA states in YFilter with bitmaps generated from set of keyword queries in CKStream. Findings – Extensive experiments were conducted using both synthetic and real data set to show the effectiveness of the proposed method. The experimental results showed that the accuracy of the proposed method was better than the baseline method (CKStream), while it consumed less memory. Moreover, the proposed scheme showed good scalability with respect to the number of queries. Originality/value – Due to the rapid diffusion of XML streams, the demand for querying such information is also growing. In such a situation, the ability to query by combining XPath and keyword search is important, because it is easy to use, but powerful means to query XML streams. However, none of existing works has addressed this issue. This work is to cope with this problem by combining an existing XPath-based YFilter and a keyword-search-based CKStream for XML streams to enable XPath-based keyword search.
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Chen, Yang, Wenmin Li, Fei Gao, Kaitai Liang, Hua Zhang, and Qiaoyan Wen. "Practical Attribute-Based Conjunctive Keyword Search Scheme." Computer Journal 63, no. 8 (December 9, 2019): 1203–15. http://dx.doi.org/10.1093/comjnl/bxz140.

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Abstract To date cloud computing may provide considerable storage and computational power for cloud-based applications to support cryptographic operations. Due to this benefit, attribute-based keyword search (ABKS) is able to be implemented in cloud context in order to protect the search privacy of data owner/user. ABKS is a cryptographic primitive that can provide secure search services for users but also realize fine-grained access control over data. However, there have been two potential problems that prevent the scalability of ABKS applications. First of all, most of the existing ABKS schemes suffer from the outside keyword guessing attack (KGA). Second, match privacy should be considered while supporting multi-keyword search. In this paper, we design an efficient method to combine the keyword search process in ABKS with inner product encryption and deploy several proposed techniques to ensure the flexibility of retrieval mode, the security and efficiency of our scheme. We later put forward an attribute-based conjunctive keyword search scheme against outside KGA to solve the aforementioned problems. We provide security notions for two types of adversaries and our construction is proved secure against chosen keyword attack and outside KGA. Finally, all-side simulation with real-world data set is implemented for the proposed scheme, and the results of the simulation show that our scheme achieves stronger security without yielding significant cost of storage and computation.
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Li, Jiguo, Min Wang, Yang Lu, Yichen Zhang, and Huaqun Wang. "ABKS-SKGA: Attribute-based keyword search secure against keyword guessing attack." Computer Standards & Interfaces 74 (February 2021): 103471. http://dx.doi.org/10.1016/j.csi.2020.103471.

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V. Kurhekar, Miss Rachana. "Analysis on Location Based Nearest Keyword Search." International Journal for Research in Applied Science and Engineering Technology V, no. II (February 28, 2017): 267–70. http://dx.doi.org/10.22214/ijraset.2017.2041.

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Lou, Ying, Feng Zhong, JinXiang Zhang, and Qian Li. "Semantic keyword search based on information entropy." Journal of Physics: Conference Series 1952, no. 4 (June 1, 2021): 042080. http://dx.doi.org/10.1088/1742-6596/1952/4/042080.

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Dissertations / Theses on the topic "Keyword-based search"

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Gopalakrishnan, Vijay. "System support for keyword-based search in structured peer-to-peer systems." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3892.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Ayvaz, Serkan. "NEAR NEIGHBOR EXPLORATIONS FOR KEYWORD-BASED SEMANTIC SEARCHES USING RDF SUMMARY GRAPH." Kent State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=kent1447710652.

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Bonetti, Lorenzo. "Design and implementation of a real-world search engine based on Okapi BM25 and SentenceBERT." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24774/.

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The work conducted in this thesis aims to present an hybrid model for a real­ world application search engine. The project presented was part of an intern­ship work carried out in a start­up which deals with Knowledge Management and Artificial Intelligence. The aim of the internship work was to improve the current search engine system to build a new system for a future web ap­plication use case. An in­-depth study on the limitations of keyword search alone, and on semantic search, revealed the need of a transition from a pure keyword­-based information retrieval system to an hybrid model, making use of both keyword search and semantic search. In particular the old system re­lied on a tfidf­-based algorithm, while the final model tries to overcome the limits of keyword search by joining the abilities of OkapiBM25, a probabilis­tic information retrieval approach, with newer semantic search models based on SentenceBERT. The models, and the algorithm implemented, exploit deeply recent techniques in Information Retrieval such as lexical search, sim­ilarity search, query expansion, document expansion and automatic question generation. The data used to test the models came from a banking dataset, be­longing to one of the company clients, previously created for an Information Retrieval chat­bot. Different experiments led to a final model able to improve the search performances showing great advantages with respect to keyword search and pure semantic search.
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Yu, Bei, Ling Liu, Beng Chin Ooi, and Kian Lee Tan. "Keyword Join: Realizing Keyword Search in P2P-based Database Systems." 2004. http://hdl.handle.net/1721.1/7423.

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In this paper, we present a P2P-based database sharing system that provides information sharing capabilities through keyword-based search techniques. Our system requires neither a global schema nor schema mappings between different databases, and our keyword-based search algorithms are robust in the presence of frequent changes in the content and membership of peers. To facilitate data integration, we introduce keyword join operator to combine partial answers containing different keywords into complete answers. We also present an efficient algorithm that optimize the keyword join operations for partial answer integration. Our experimental study on both real and synthetic datasets demonstrates the effectiveness of our algorithms, and the efficiency of the proposed query processing strategies.
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Hina, Manolo Dulva. "Keyword-based approaches to improve internet search." Thesis, 2003. http://spectrum.library.concordia.ca/2023/1/MQ77713.pdf.

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Technology keeps on evolving and so must the science of information retrieval. This thesis presents keyword-based approaches to improve information retrieval from the Internet. Focused and unfocused queries to search engines are considered, and means of obtaining relevant documents are presented. For focused queries, techniques are provided to obtain a high precision score from the hit documents; these documents do contain the exact answers to the focused query, which is usually a question. User queries are subjected to ambiguity test to determine if it is ambiguous, and if it is so, provide direction so as the user's intended meaning is the one that is actually searched. The queries are modified to form a new clear and unambiguous. Query is sent to several search engines at the same time, and hit documents from each of these search engines are collated and merged. Hit documents to an ambiguous query are analyzed and ranked based on their actual relevance to the query. Term frequency is used, along with popularity score, to determine the total score of a relevant document. Every relevant hit document is classified based on its academic relevance. A few academic categories are considered--(1) Course Notes, (2) Frequently Asked Questions, (3) Research Paper, (4) Technical Report, (5) Thesis, (6) Tutorial, (7) Review, and (8) Research Paper/Technical Report. Once a search is done, a set of relevant documents is presented, along with each document's academic relevance category (if any)
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Wen, Ting-Hui, and 溫玎薈. "Identity-Based Broadcast Encryption Scheme with Keyword Search." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/07603382282619045997.

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Fang, Chien-Tse, and 方建喆. "Keyword Search on DHT-based Peer-to-Peer Networks." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/76897307036461519101.

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碩士
國立臺灣大學
資訊管理研究所
92
Abstract Peer-to-peer search is to search for objects on a peer-to-peer network according to application-defined semantics. It is a challenging problem because the advantages of a peer-to-peer network are to be preserved while feasible performance must be achieved. A DHT is a distributed name resolution architecture for a peer-to-peer network of Internet-scale; however, it does not possess search ability. Some work tries to build global inverted indexes on a DHT in order to provide keyword search ability, but these approaches suffer from severe unbalanced load at each node. It is due to the power-law nature of any document set. Semantic routing, in which each node based on locally collected information forwards received queries to only those neighbors that are semantically close to the queries, is another category of solutions to peer-to-peer search problems. These approaches often adopt sophisticated information retrieval algorithms to guide message forwarding on Gnutella-like peer-to-peer networks. Semantic routing is more precise in terms of document retrieval than global inverted indexing, but is inefficient when the network size scales to the Internet size. We propose a keyword search scheme on DHT-based peer-to-peer network in order to scale our solution to the Internet size. Our scheme is to index objects according their associated keyword sets with Bloom filter techniques. Each object is represented as an r-bit filter vector. In the meantime, we build an r-dimensional hypercubic keyword search layer on top of a DHT. Then we place each object on the hypercube according to its filter vector. Our approach is proved to provide the function of a global inverted index but achieves much better load balance than previous work even under the power-law nature of an object set. The hypercubic keyword search layer also implies index closeness in its topology, which improves search performance when only a portion of query-satisfying objects are needed. Each query made can be resolved within logarithmic hop counts, and the cost to resolve a query is linear to the resultant set size of the query.
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Hsieh, Fei-Ju, and 謝斐如. "Semantics-based Multi-Keyword Search over Encrypted Cloud Data." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/q58x9g.

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碩士
國立臺灣科技大學
資訊工程系
105
Cloud storages have gained popularity in the recent years. With the increasing quantity of data outsourced to cloud storages, keyword search over encrypted cloud data with the consideration of privacy preservation has become an important topic. The majority techniques in the literature only provide exact single or multiple keyword search in which the keywords have to exactly match those in a pre-defined dictionary. However, restricting users’keywords within the pre-defined dictionary is impractical for real-world applications. Some existing fuzzy keyword search schemes only focus on dealing with spelling mistakes of keywords. The flexibility of keywords used in the search is not considered. This paper addresses the problem of semantic multi-keyword search over encrypted cloud data. Users can use keywords not just in the pre-defined dictionary of the dataset, but with the flexibility of their own choice. The similarity of the given keywords with the search index of each document is then calculated. An adequate set of documents are selected as the results for the search based on the similarity. In addition, privacy of the search is also considered during the search executed by the third party service provider. Experiments are conducted using a dataset of massive papers in real world. The experimental analyses show that the proposed scheme can perform the semantic multi-keyword search effectively and efficiently.
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HUANG, CHUN-HAO, and 黃俊豪. "A Study of Relation based Indexing on XML Keyword Search." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/12336068616624294886.

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碩士
中原大學
資訊工程研究所
96
XML is becoming the standard for data exchanges and data representation. Keyword search allows a user to easily query and access XML data and thus becomes an important research issue. In this thesis, we used Dewey-base two indices to index XML data. It does not require re-computation of existing labels when an XML document is updated. When returning keyword search results, we use the relationships between nodes ensure the return data is correct and to avoid returning meaningless data. Users can query XML data without having to understand the XML structure. An example system was implemented as an illustration.
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Guo, Min-Siang, and 郭民翔. "An Iconic Keyword-based Storybook Search System for Young Children." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/69425568898840747588.

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碩士
清雲科技大學
資訊管理所
100
According to Nielsen Online research report, children online population grew 18 percent over the past five years. Storybooks have been the main source of children reading. With the advance of digital contents and computer technologies, how young children choose their interest digital storybooks in a digital library or on the Internet is becoming important. However, children often encounter difficulties in finding books with traditional keyword search interfaces due to the immaturity of cognitive development. Therefore, the purpose of this study is to develop an intuitive, iconic keyword search interface with which children compose comprehensible image keywords for their intended storybooks. This study also investigates the usability of the iconic keyword-based storybook search system for young children. The evaluation of the system involved 20 kindergarten and 20 second grade elementary children. The evaluation results showed that kindergarten children composed their search terms mainly based on characters on the book covers in both tasks of finding favorite storybooks and searching specific storybooks. However, the elementary children showing their imagination and observation demonstrated more detailed search terms by including elements of scenes of a book cover in the aforementioned tasks. For the usability aspect, elementary children showed higher rates of task completion and correctness of usability questions.
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Books on the topic "Keyword-based search"

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Cardoso, Jorge, Francesco Guerra, Geert-Jan Houben, Alexandre Miguel Pinto, and Yannis Velegrakis, eds. Semantic Keyword-based Search on Structured Data Sources. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27932-9.

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Calì, Andrea, Dorian Gorgan, and Martín Ugarte, eds. Semantic Keyword-Based Search on Structured Data Sources. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53640-8.

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Szymański, Julian, and Yannis Velegrakis, eds. Semantic Keyword-Based Search on Structured Data Sources. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74497-1.

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Cardoso, Jorge, Francesco Guerra, Yannis Velegrakis, Geert-Jan Houben, and Alexandre Miguel Pinto. Semantic Keyword-based Search on Structured Data Sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, ... Springer, 2016.

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Velegrakis, Yannis, and Julian Szymański. Semantic Keyword-Based Search on Structured Data Sources: Third International KEYSTONE Conference, IKC 2017, Gdańsk, Poland, September 11-12, 2017, ... Springer, 2018.

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Cardoso, Jorge, Francesco Guerra, Yannis Velegrakis, Geert-Jan Houben, and Alexandre Miguel Pinto. Semantic Keyword-Based Search on Structured Data Sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Springer London, Limited, 2016.

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Calì, Andrea, Dorian Gorgan, and Martín Ugarte. Semantic Keyword-Based Search on Structured Data Sources: Second COST Action IC1302 International KEYSTONE Conference, IKC 2016, Cluj-Napoca, Romania, September 8-9, 2016, Revised Selected Papers. Springer, 2017.

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Book chapters on the topic "Keyword-based search"

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Yu, Jeffrey Xu, Lu Qin, and Lijun Chang. "Graph-Based Keyword Search." In Keyword Search in Databases, 45–81. Cham: Springer International Publishing, 2010. http://dx.doi.org/10.1007/978-3-031-79426-1_3.

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Chang, George, Marcus J. Healey, James A. M. McHugh, and Jason T. L. Wang. "Keyword-Based Search Engines." In Mining the World Wide Web, 3–18. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1639-2_1.

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Weiand, Klara, Andreas Hartl, Steffen Hausmann, François Bry, and Tim Furche. "Keyword-Based Search over Semantic Data." In Semantic Search over the Web, 159–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25008-8_7.

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Li, Jie, Mimi Ma, Jiang Zhang, Shuqin Fan, and Shuaigang Li. "Attribute-Based Keyword Search from Lattices." In Information Security and Cryptology, 66–85. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42921-8_4.

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Stanković, Ranka, Cvetana Krstev, Duško Vitas, Nikola Vulović, and Olivera Kitanović. "Keyword-Based Search on Bilingual Digital Libraries." In Semantic Keyword-Based Search on Structured Data Sources, 112–23. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53640-8_10.

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Ouksili, Hanane, Zoubida Kedad, Stéphane Lopes, and Sylvaine Nugier. "Pattern-Based Keyword Search on RDF Data." In The Semantic Web, 30–34. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47602-5_7.

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Liu, Xueyan, Tingting Lu, Xiaomei He, and Xiaotao Yang. "Multi-keyword Search Based on Attribute Encryption." In Web Information Systems and Applications, 340–46. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30952-7_34.

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Sartori, Enrico, Yannis Velegrakis, and Francesco Guerra. "Entity-Based Keyword Search in Web Documents." In Lecture Notes in Computer Science, 21–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49521-6_2.

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Geist, Ingolf. "Index-Based Keyword Search in Mediator Systems." In Current Trends in Database Technology - EDBT 2004 Workshops, 24–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30192-9_3.

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Kasra Kermanshahi, Shabnam, Joseph K. Liu, and Ron Steinfeld. "Multi-user Cloud-Based Secure Keyword Search." In Information Security and Privacy, 227–47. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60055-0_12.

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Conference papers on the topic "Keyword-based search"

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Xie, Xike, Xin Lin, Jianliang Xu, and Christian S. Jensen. "Reverse Keyword-Based Location Search." In 2017 IEEE 33rd International Conference on Data Engineering (ICDE). IEEE, 2017. http://dx.doi.org/10.1109/icde.2017.96.

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Hagen, Matthias, and Benno Stein. "Search Strategies for Keyword-based Queries." In 2010 21st International Conference on Database and Expert Systems Applications (DEXA). IEEE, 2010. http://dx.doi.org/10.1109/dexa.2010.29.

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Sari, Leda, Batuhan Gundogdu, and Murat Saraclar. "Posteriorgram based approaches in keyword search." In 2015 23th Signal Processing and Communications Applications Conference (SIU). IEEE, 2015. http://dx.doi.org/10.1109/siu.2015.7130048.

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Yousefipoor, Vahid, Mohammad Hassan Ameri, Javad Mohajeri, and Taraneh Eghlidos. "A secure attribute based keyword search scheme against keyword guessing attack." In 2016 8th International Symposium on Telecommunications (IST). IEEE, 2016. http://dx.doi.org/10.1109/istel.2016.7881795.

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Chen, I.-Fan, Chongjia Ni, Boon Pang Lim, Nancy F. Chen, and Chin-Hui Lee. "A keyword-aware grammar framework for LVCSR-based spoken keyword search." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178962.

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Gundogdu, Batuhan, Leda Sari, Gozde Cetinkaya, and Murat Saraclar. "Template-based Keyword Search with pseudo posteriorgrams." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7495904.

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Chen, Yi, Wei Wang, and Ziyang Liu. "Keyword-based search and exploration on databases." In 2011 IEEE International Conference on Data Engineering (ICDE 2011). IEEE, 2011. http://dx.doi.org/10.1109/icde.2011.5767958.

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Li, Runhe, Dong Zheng, Yinghui Zhang, Haonan Su, Menglei Yang, and Pengzhen Lang. "Attribute-Based Encryption with Multi-keyword Search." In 2017 IEEE Second International Conference on Data Science in Cyberspace (DSC). IEEE, 2017. http://dx.doi.org/10.1109/dsc.2017.97.

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Ko, Jihoon, Sangjin Shin, Sungkwang Eom, Minjae Song, Jooik Jung, Dong Hoon Shin, Kyong Ho Lee, and Yongil Jang. "Keyword Based Semantic Search for Mobile Data." In 2014 15th IEEE International Conference on Mobile Data Management (MDM). IEEE, 2014. http://dx.doi.org/10.1109/mdm.2014.36.

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Muzdalifa, Annisa, and G. A. Putri Saptawati. "Keyword Search System Based On Klustree Method." In 2019 International Conference on Data and Software Engineering (ICoDSE). IEEE, 2019. http://dx.doi.org/10.1109/icodse48700.2019.9092743.

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Reports on the topic "Keyword-based search"

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Bolton, Laura. Initiatives for the Governance of the Covid-19 Vaccine Rollout, with Special Reference to Social Inclusion. Institute of Development Studies, March 2022. http://dx.doi.org/10.19088/cc.2021.007.

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Abstract:
This rapid review was sourced from key websites and used some keyword searching whilst making an effort to filter out news and media. As systematic searching is not possible within the scope of this review, it cannot be considered a comprehensive listing of activity in the area of vaccine rollout. It is also likely that initiatives and support are occurring which are unpublished. This report should, therefore, be considered a snapshot of activity in this area. It comprises a list of what was found and cannot make assertions about inactivity based on what was not found. The question asked for ‘initiatives’ to be identified, and it has been interpreted broadly. The search identified reports describing support for rollouts, published guidelines, frameworks, calls to action and opinion pieces. The information is organised by institution type. Often information was in the form of a news piece or blog rather than formal documentation, as the situation is current and unfolding and recent information is only available in this type of media. Vaccine passports were outside of the scope of this review.
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