Relevant bibliographies by topics / Keyword search over XML

Contents

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

Academic literature on the topic 'Keyword search over XML'

Author: Grafiati
Published: 19 February 2023
Last updated: 20 February 2023

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Journal articles on the topic "Keyword search over XML"

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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 (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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Le, Thuy Ngoc, and Tok Wang Ling. "Survey on Keyword Search over XML Documents." ACM SIGMOD Record 45, no. 3 (2016): 17–28. http://dx.doi.org/10.1145/3022860.3022863.

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Shao, Feng, Lin Guo, Chavdar Botev, et al. "Efficient keyword search over virtual XML views." VLDB Journal 18, no. 2 (2009): 543–70. http://dx.doi.org/10.1007/s00778-008-0126-x.

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Zhao, Yue, Ye Yuan, and Guoren Wang. "Keyword Search over Probabilistic XML Documents Based on Node Classification." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/210961.

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This paper describes a keyword search measure on probabilistic XML data based on ELM (extreme learning machine). We use this method to carry out keyword search on probabilistic XML data. A probabilistic XML document differs from a traditional XML document to realize keyword search in the consideration of possible world semantics. A probabilistic XML document can be seen as a set of nodes consisting of ordinary nodes and distributional nodes. ELM has good performance in text classification applications. As the typical semistructured data; the label of XML data possesses the function of definition itself. Label and context of the node can be seen as the text data of this node. ELM offers significant advantages such as fast learning speed, ease of implementation, and effective node classification. Set intersection can compute SLCA quickly in the node sets which is classified by using ELM. In this paper, we adopt ELM to classify nodes and compute probability. We propose two algorithms that are based on ELM and probability threshold to improve the overall performance. The experimental results verify the benefits of our methods according to various evaluation metrics.
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Rathod, Supriya C., and Sonali M. Tidke. "Survey on Interactive Keyword Search Over XML Data to Obtain Top-K Results." Indian Journal of Applied Research 4, no. 3 (2011): 158–60. http://dx.doi.org/10.15373/2249555x/mar2014/46.

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Yang, Weidong, Fei Fang, Nan Li, and Zhongyu (Joan) Lu. "XKFitler." International Journal of Information Retrieval Research 1, no. 1 (2011): 1–18. http://dx.doi.org/10.4018/ijirr.2011010101.

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Most existing XML stream processing systems adopt full structured query languages, such as XPath or XQuery, but they are difficult for ordinary users to learn and use. Keyword search is a user-friendly information discovery technique that has been extensively studied for text documents. This paper presents an XML stream filter system called XKFitler, which is the first system for supporting keyword search over XML stream. In XKFitler, the concepts of XLCA (eXclusive Lowest Common Ancestor) and XLCA Connecting Tree (XLCACT) are used to define the search semantic and results of keywords, and present an approach to filter XML stream according to keywords. The prototype XKFilter is implemented in the experiments.
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Sun, Dong-Han, and Soo-Chan Hwang. "A Labeling Methods for Keyword Search over Large XML Documents." Journal of KIISE 41, no. 9 (2014): 699–706. http://dx.doi.org/10.5626/jok.2014.41.9.699.

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Liu, Xiping. "Semantics Oriented Inference of Keyword Search Intention over XML Documents." Information Technology Journal 12, no. 1 (2012): 51–60. http://dx.doi.org/10.3923/itj.2013.51.60.

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WANG, Yang, Zhikui CHEN, and Xiaodi HUANG. "Element Retrieval Using Namespace Based on Keyword Search over XML Documents." Journal of Software Engineering and Applications 03, no. 01 (2010): 65–72. http://dx.doi.org/10.4236/jsea.2010.31008.

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Tekli, Joe, Gilbert Tekli, and Richard Chbeir. "Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying." Computer Science and Information Systems, no. 00 (2022): 63. http://dx.doi.org/10.2298/csis220228063t.

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Many efforts have been deployed by the IR community to extend free-text query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. In this paper, we describe a new approach for XML keyword search aiming to solve the limitations mentioned above. Our solution first transforms the XML document collection (offline) and the keyword query (on-the-fly) into meaningful semantic representations using context-based and global disambiguation methods, specially designed to allow almost linear computation efficiency. We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. Experimental results highlight the quality and potential of our approach.
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Dissertations / Theses on the topic "Keyword search over XML"

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Li, Sheng. "Query Suggestion for Keyword Search over XML and RDF Data." Thesis, Griffith University, 2014. http://hdl.handle.net/10072/367139.

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With the growing amount of XML and RDF data, keyword search over XML and RDF data has become an important and increasingly researched topic. In this thesis, we investigate several problems related to keyword search over XML and RDF data, and provide solutions to these problems. The research consists largely of three main technical contributions: top-k nearest keyword (NK) search for XML data, query suggestion for XML data and query suggestion for RDF data. We first study the top-k NK search problem for XML data, which provides an approach to exploring XML queries by the distance between keyword matching nodes. A top-k NK query is to find the top-k nearest neighbors of a given node where each neighbor matches a certain keyword, and it can serve as the building block to deal with many problems in XML data, such as keyword search. In our research, we design a method to construct an extended compact TVP (ecTVP) index to efficiently find the top-k nearest neighbors in XML data. We build the index by constructing a variant of Extended Compact Tree, which finds the top-k nearest neighbors during a bottom-up and a top-down process. Theoretical analysis and experiments indicate that our proposed method is efficient to build the ecTVP index. Moreover, we reduce the redundancy in the ecTVP index. In this way, the index costs less space and query time.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Information and Communication Technology<br>Science, Environment, Engineering and Technology<br>Full Text
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Markowetz, Alexander. "Keyword search over relational data /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20MARKOW.

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IZQUIERDO, YENIER TORRES. "KEYWORD SEARCH OVER FEDERATED RDF GRAPHS BY EXPLORING THEIR SCHEMAS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30739@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>O Resource Description Framework (RDF) foi adotado como uma recomendação do W3C em 1999 e hoje é um padrão para troca de dados na Web. De fato, uma grande quantidade de dados foi convertida em RDF, muitas vezes em vários conjuntos de dados fisicamente distribuídos ao longo de diferentes localizações. A linguagem de consulta SPARQL (sigla do inglês de SPARQL Protocol and RDF Query Language) foi oficialmente introduzido em 2008 para recuperar dados RDF e fornecer endpoints para consultar fontes distribuídas. Uma maneira alternativa de acessar conjuntos de dados RDF é usar consultas baseadas em palavras-chave, uma área que tem sido extensivamente pesquisada, com foco recente no conteúdo da Web. Esta dissertação descreve uma estratégia para compilar consultas baseadas em palavras-chave em consultas SPARQL federadas sobre conjuntos de dados RDF distribuídos, assumindo que cada conjunto de dados RDF tem um esquema e que a federação tem um esquema mediado. O processo de compilação da consulta SPARQL federada é explicado em detalhe, incluindo como computar o conjunto de joins externos entre as subconsultas locais geradas, como combinar, com a ajuda de cláusulas UNION, os resultados de consultas locais que não têm joins entre elas, e como construir a cláusula TARGET, de acordo com a composição da cláusula WHERE. Finalmente, a dissertação cobre experimentos com dados do mundo real para validar a implementação.<br>The Resource Description Framework (RDF) was adopted as a W3C recommendation in 1999 and today is a standard for exchanging data in the Web. Indeed, a large amount of data has been converted to RDF, often as multiple datasets physically distributed over different locations. The SPARQL Protocol and RDF Query Language (SPARQL) was officially introduced in 2008 to retrieve RDF datasets and provide endpoints to query distributed sources. An alternative way to access RDF datasets is to use keyword-based queries, an area that has been extensively researched, with a recent focus on Web content. This dissertation describes a strategy to compile keyword-based queries into federated SPARQL queries over distributed RDF datasets, under the assumption that each RDF dataset has a schema and that the federation has a mediated schema. The compilation process of the federated SPARQL query is explained in detail, including how to compute a set of external joins between the local subqueries, how to combine, with the help of the UNION clauses, the results of local queries which have no external joins between them, and how to construct the TARGET clause, according to the structure of the WHERE clause. Finally, the dissertation covers experiments with real-world data to validate the implementation.
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Oliveira, Péricles Silva de, and 21-98498-9543. "Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases." Universidade Federal do Amazonas, 2017. http://tede.ufam.edu.br/handle/tede/5806.

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Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-08-22T19:40:10Z No. of bitstreams: 2 Tese - Péricles Silva de Oliveira.pdf: 1875380 bytes, checksum: 014ba89b7fe1929a1461c9d8d3959416 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-08-22T19:40:26Z (GMT) No. of bitstreams: 2 Tese - Péricles Silva de Oliveira.pdf: 1875380 bytes, checksum: 014ba89b7fe1929a1461c9d8d3959416 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2017-08-22T19:40:44Z (GMT) No. of bitstreams: 2 Tese - Péricles Silva de Oliveira.pdf: 1875380 bytes, checksum: 014ba89b7fe1929a1461c9d8d3959416 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2017-08-22T19:40:44Z (GMT). No. of bitstreams: 2 Tese - Péricles Silva de Oliveira.pdf: 1875380 bytes, checksum: 014ba89b7fe1929a1461c9d8d3959416 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-04-28<br>Several systems proposed for processing keyword queries over relational databases rely on the generation and evaluation of Candidate Networks (CNs), i.e., networks of joined database relations that, when processed as SQL queries, provide a relevant answer to the input keyword query. Although the evaluation of CNs has been extensively addressed in the literature, problems related to efficiently generating meaningful CNs have received much less attention. To generate useful CNs is necessary to automatically locating, given a handful of keywords, relations in the database that may contain relevant pieces of information, and determining suitable ways of joining these relations to satisfy the implicit information need expressed by a user when formulating her query. In this thesis, we present two main contributions related to the processing of Candidate Networks. As our first contribution, we present a novel approach for generating CNs, in which possible matchings of the query in database are efficiently enumerated at first. These query matches are then used to guide the CN generation process, avoiding the exhaustive search procedure used by current state-of-art approaches. We show that our approach allows the generation of a compact set of CNs that leads to superior quality answers, and that demands less resources in terms of processing time and memory. As our second contribution, we initially argue that the number of possible Candidate Networks that can be generated by any algorithm is usually very high, but that, in fact, only very few of them produce answers relevant to the user and are indeed worth processing. Thus, there is no point in wasting resources processing useless CNs. Then, based on such an argument, we present an algorithm for ranking CNs, based on their probability of producing relevant answers to the user. This relevance is estimated based on the current state of the underlying database using a probabilistic Bayesian model we have developed. By doing so we are able do discard a large number of CNs, ultimately leading to better results in terms of quality and performance. Our claims and proposals are supported by a comprehensive set of experiments we carried out using several query sets and datasets used in previous related work and whose results we report and analyse here.<br>Sem resumo.
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Manica, Edimar. "Suporte a consultas temporais por palavras-chave em documentos XML." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2010. http://hdl.handle.net/10183/27664.

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Consultas por palavras-chave permitem o acesso fácil a dados XML, uma vez que não exigem que o usuário aprenda uma linguagem de consulta estruturada nem estude possíveis esquemas de dados complexos. Com isso, vários motores de busca XML foram propostos para permitir a extração de fragmentos XML relevantes para consultas por palavras-chave. No entanto, esses motores de busca tratam as expressões temporais da mesma forma que qualquer outra palavra-chave. Essa abordagem ocasiona inúmeros problemas, como por exemplo, considerar como casamentos para uma expressão temporal nodos do domínio preço ou código. Este trabalho descreve TPI (Two Phase Interception), uma abordagem que permite o suporte a consultas temporais por palavras-chave em documentos XML orientados a dados. O suporte a consultas temporais é realizado através de uma camada adicional de software que executa duas interceptações no processamento de consultas, realizado por um motor de busca XML. Esta camada adicional de software é responsável pelo tratamento adequado das informações temporais presentes na consulta e no conteúdo dos documentos XML. O trabalho ainda especifica TKC (Temporal Keyword Classification), uma classificação de consultas temporais que serve de guia para qualquer mecanismo de consulta por palavras-chave, inclusive TPI. São apresentados os algoritmos de mapeamento das diferentes formas de predicados temporais por palavras-chave, especificadas em TKC, para expressões relacionais a fim de orientar a implementação do processamento das consultas temporais. É proposto um índice temporal e definidas estratégias para identificação de caminhos temporais, desambiguação de formatos de valores temporais, identificação de datas representadas por vários elementos e identificação de intervalos temporais. São demonstrados experimentos que comparam a qualidade, o tempo de processamento e a escalabilidade de um motor de busca XML com e sem a utilização de TPI. A principal contribuição desse trabalho é melhorar significativamente a qualidade dos resultados de consultas temporais por palavras-chave em documentos XML.<br>Keyword queries enable users to easily access XML data, since the user does not need to learn a structured query language or study possibly complex data schemas. Therewith, several XML search engines have been proposed to extract relevant XML fragments in response to keyword queries. However, these search engines treat the temporal expressions as any other keyword. This approach may lead to several problems. It could, for example, consider prices and codes as matches to a temporal expression. This work describes TPI (Two Phase Interception), an approach that supports temporal keyword queries on data-centric XML documents. The temporal query support is performed by adding an additional software layer that executes two interceptions in the query processing performed by a XML search engine. This additional software layer is responsible for the adequate treatment of the temporal expressions contained in the query and in the contents of the XML documents. This work also specifies TKC (Temporal Keyword Classification), a temporal query classification to be used as guidance for any keyword query mechanism, including TPI. We present the algorithms for mapping different temporal predicates expressed by keywords to relational expressions in order to guide the implementation of the temporal query processing. We propose a temporal index together with strategies to perform temporal path identification, format disambiguation, identification of dates represented by many elements and detection of temporal intervals. This work also reports on experiments which evaluate quality, processing time and scalability of an XML search engine with TPI and without TPI. The main contribution of this work is the significant improvement in the quality of the results of temporal keyword queries on XML documents.
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Luo, Chieh-Chang, and 羅介璋. "Supporting Structural and Keyword Search for XML Data." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/85328509214377290085.

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碩士<br>國立臺灣海洋大學<br>資訊工程學系<br>94<br>Abstract In this thesis, we discuss how to use the technology of Information Retrieval to combine with the XQuery Query Processing algorithm, so that we could retrieve the data that conforms the structural and value constraints imposed by users. To process the structural constraints, we propose to decompose the query tree into a sequence of suffix paths. Each suffix path consists of only parent-child relationship between nodes. Then, the system will retrieve elements that correspond to each suffix path, and combine those elements to form the final result. The XML data will be pre-processed and represented in the internal form. Basically, we assign each possible path in XML data a P-Label. Each path is associated with an Element-Encoding table, which records the structural and value information for all the elements which correspond to this P-Label. To meet the requirement of information retrieval, we adopt the BM25 Scoring Model to pre-compute the scores between elements and keywords and store the scores within the associated Element-Encoding Table. Therefore, we can efficiently determine if the element’s keyword satisfies user’s value constraint and find the corresponding score. We have performed a series of experiments to evaluate the performance of the proposed approach. We also contrast with a well-known system. The experimental results show that our system is very efficient.
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Chien, Po-Hsien, and 簡伯先. "The Research on Identifying Contributors for XML Keyword Search." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/69083781335331784410.

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碩士<br>國立臺灣海洋大學<br>資訊工程學系<br>99<br>It is important to satisify one's information needs with compact returning results when users input keyword queries. [LC08] proposed the MaxMatch system which has been widly discussed and applied. In this thesis, we will discuss how to efficiently generate the results defined by [LC08]. Two systems, TDPrune and LevelPrune, are designed to improve the performance by reducing the nodes to process. We also propose several improvements based on storage and compression techniques to further reduce the query processing time. We then implement the two systems and LevelPrune+, which improves the LevelPrune system by applying the proposed storage and compression techniques. Finally, we design a series of experiments to compare the three systems with MaxMatch and analyze the pros and cons of each system. The experiment results show that all our systems are more effiecient then MaxMatch, and LevelPrune+ is usually the most effiecient one.
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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<br>中原大學<br>資訊工程研究所<br>96<br>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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Feng, Zhisheng. "Xpareto : a text-centric XML search engine /." 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR38770.

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Thesis (M.Sc.)--York University, 2007. Graduate Programme in Computer Science and Engineering.<br>Typescript. Includes bibliographical references (leaves 187-189). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR38770
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Li, Chun-Yi, and 李俊毅. "Identifying Relevant Matches for XML Keyword Search with and-or Operators." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/82207516531149534518.

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碩士<br>國立臺灣海洋大學<br>資訊工程學系<br>98<br>In this thesis, we discuss how to produce the desirable results for queries which consist of keywords combined by the “AND” operator and the “OR” operator. We consider two properties: monotoncity and consistency, which describe the desirable change to the number of query results or the content of query results upon update to the data or query. We also propose a corresponding algorithm. It first divides a query into clauses and keywords. According to the four cases for matches under each node, it then compares the clause set and keyword set of each node with its sibling to decide whether to output or not. We have implemented the algorithm, and performed a series of experiments to show the effectiveness and efficiency of the proposed approach.
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Books on the topic "Keyword search over XML"

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Lu, Jiaheng. An Introduction to XML Query Processing and Keyword Search. Springer Berlin Heidelberg, 2013.

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Lu, Jiaheng. An Introduction to XML Query Processing and Keyword Search. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34555-5.

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Lu, Jiaheng. An Introduction to XML Query Processing and Keyword Search. Springer, 2015.

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An Introduction To Xml Query Processing And Keyword Search. Springer-Verlag Berlin and Heidelberg GmbH &, 2012.

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Lu, Jiaheng. An Introduction to XML Query Processing and Keyword Search. Springer, 2013.

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Ray, Amit Shovon, M. Parameswaran, Manmohan Agarwal, et al. Quality of Social Science Research in India. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199474417.003.0007.

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The chapter analyses the quality of research in terms of quality of articles and of journals by using a quality index. It uses two-dimension indicators to judge the quality of articles, that is, citations (scholarly) and readership, which is the number of hits an article receives in a simple Google keyword search. The quality of a journal is measured in terms of three dimensions: its presence over time, its presence across space, and its depth. The study took 21351 journal articles from 1006 journals (902 journals from Scopus and 104 journals from ISID for five-year period, 2010–14. It emerged that India’s social science research (SSR) contributes more to public debates and policy formulations and relatively less in pushing the frontiers of knowledge for further research.
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Book chapters on the topic "Keyword search over XML"

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Zhang, Linlin, Qing Liu, and Jiaheng Lu. "Effective Keyword Search with Synonym Rules over XML Document." In Web-Age Information Management. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33050-6_28.

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Lu, Jiaheng. "Effective XML Keyword Search." In An Introduction to XML Query Processing and Keyword Search. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34555-5_6.

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Wu, Huayu, and Zhifeng Bao. "Object-Oriented XML Keyword Search." In Conceptual Modeling – ER 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24606-7_30.

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Lu, Jiaheng. "XML Keyword Pattern Refinement." In An Introduction to XML Query Processing and Keyword Search. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34555-5_7.

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Le, Thuy Ngoc, Zhifeng Bao, and Tok Wang Ling. "Schema-Independence in XML Keyword Search." In Conceptual Modeling. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12206-9_6.

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Le, Thuy Ngoc, Tok Wang Ling, H. V. Jagadish, and Jiaheng Lu. "Object Semantics for XML Keyword Search." In Database Systems for Advanced Applications. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05813-9_21.

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Tian, Zongqi, Jiaheng Lu, and Deying Li. "A Survey on XML Keyword Search." In Web Technologies and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20291-9_52.

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Casanova, Marco A. "Keyword Search over RDF Datasets." In Conceptual Modeling. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33223-5_2.

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Wang, Dong, Lei Zou, Wanqiong Pan, and Dongyan Zhao. "Keyword Graph: Answering Keyword Search over Large Graphs." In Advanced Data Mining and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35527-1_53.

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Chang, Ya-Hui, Po-Hsien Chien, and Yu-Kai Chang. "Efficiently Identifying Contributors for XML Keyword Search." In Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29038-1_15.

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Conference papers on the topic "Keyword search over XML"

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Yue Zhao, Guoren Wang, Ye Yuan, Junxia Wang, Chungang Lin, and Ying Yu. "Keyword search over probabilistic XML data." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015. http://dx.doi.org/10.1109/fskd.2015.7382118.

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Yue Zhao, Guoren Wang, and Ye Yuan. "Fuzzy keyword search over probabilistic XML data." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015. http://dx.doi.org/10.1109/fskd.2015.7382352.

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Yang, Weidong, and Baile Shi. "Schema-Aware Keyword Search over XML Streams." In 7th IEEE International Conference on Computer and Information Technology (CIT 2007). IEEE, 2007. http://dx.doi.org/10.1109/cit.2007.119.

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Liru Zhang, Tadashi Ohmori, and Mamoru Hoshi. "Keyword search over hybrid XML-relational databases." In SICE 2008 - 47th Annual Conference of the Society of Instrument and Control Engineers of Japan. IEEE, 2008. http://dx.doi.org/10.1109/sice.2008.4654630.

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Li, Jianxin, Chengfei Liu, Rui Zhou, and Wei Wang. "Top-k keyword search over probabilistic XML data." In 2011 IEEE International Conference on Data Engineering (ICDE 2011). IEEE, 2011. http://dx.doi.org/10.1109/icde.2011.5767875.

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Agarwal, Manoj K., and Krithi Ramamritham. "Enabling generic keyword search over raw XML data." In 2015 IEEE 31st International Conference on Data Engineering (ICDE). IEEE, 2015. http://dx.doi.org/10.1109/icde.2015.7113410.

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Ling, Tok Wang, Thuy Ngoc Le, and Zhong Zeng. "Semantics-based keyword search over XML and relational databases." In the Fourth Symposium. ACM Press, 2013. http://dx.doi.org/10.1145/2542050.2542054.

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Bou, Savong, Toshiyuki Amagasa, and Hiroyuki Kitagawa. "Keyword Search with Path-Based Filtering over XML Streams." In 2014 IEEE 33rd International Symposium on Reliable Distributed Systems (SRDS). IEEE, 2014. http://dx.doi.org/10.1109/srds.2014.63.

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Li, Guoliang, Jianhua Feng, Jianyong Wang, and Lizhu Zhou. "Effective keyword search for valuable lcas over xml documents." In the sixteenth ACM conference. ACM Press, 2007. http://dx.doi.org/10.1145/1321440.1321447.

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Lou, Ying, Zhanhuai Li, Meng Han, and Juan Xu. "Effective Keyword Search for Precise Return Information over XML Documents." In 2009 WRI Global Congress on Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/gcis.2009.319.

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