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Relevant bibliographies by topics / Search Indexing

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Academic literature on the topic 'Search Indexing'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Search Indexing"

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Researcher. "DEMYSTIFYING SEARCH INDEXING AND RANKING." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 166–74. https://doi.org/10.5281/zenodo.13934942.

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This article explores the intricate processes of search indexing and ranking, which form the backbone of modern search engine technology. It traces the evolution of search engine performance from 2010 to 2022, highlighting significant improvements in web page indexing, search speed, and user satisfaction. The article delves into the key components of search indexing, including content crawling, analysis, index creation, and maintenance, emphasizing recent advancements in natural language processing and machine learning. It then examines search ranking algorithms, discussing crucial factors suc

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Lashkari, Fatemeh, Faezeh Ensan, Ebrahim Bagheri, and Ali A. Ghorbani. "Efficient indexing for semantic search." Expert Systems with Applications 73 (May 2017): 92–114. http://dx.doi.org/10.1016/j.eswa.2016.12.033.

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PRATT, KEVIN B., and EUGENE FINK. "SEARCH FOR PATTERNS IN COMPRESSED TIME SERIES." International Journal of Image and Graphics 02, no. 01 (2002): 89–106. http://dx.doi.org/10.1142/s0219467802000482.

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We describe a technique for fast compression of time series, indexing of compressed series, and retrieval of series similar to a given pattern. The compression procedure identifies "important" points of a series and discards the other points. We use the important points not only for compression, but also for indexing a database of time series. Experiments show the effectiveness of this technique for indexing of stock prices, weather data and electroencephalograms.

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Safaei, Ali Asghar, and Saeede Habibi-Asl. "Multidimensional indexing technique for medical images retrieval." Intelligent Data Analysis 25, no. 6 (2021): 1629–66. http://dx.doi.org/10.3233/ida-205495.

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Retrieving required medical images from a huge amount of images is one of the most widely used features in medical information systems, including medical imaging search engines. For example, diagnostic decision making has traditionally been accompanied by patient data (image or non-image) and previous medical experiences from similar cases. Indexing as part of search engines (or retrieval system), increases the speed of a search. The goal of this study, is to provide an effective and efficient indexing technique for medical images search engines. In this paper, in order to archive this goal, a

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Sandip, Ghosh. "IMPLICATIONS OF KWWIICC (MODIFIED KWIC) INDEXING SYSTEM TO JUSTIFY RETRIEVALS OF SEARCH ENGINES." International Journal of Computational Research and Development (IJCRD) 5, no. 2 (2020): 8–13. https://doi.org/10.5281/zenodo.4311583.

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KWWIICC (modified KWIC) is an updated version to search engines to address the main problem of document Retrieval i.e. high recall and low precision. It tries to modify the definition of precision and precise document as per user intent. It establishes a new structure of indexing-retrieval mechanism which inspires search engines to serve documents in a new manner i.e. relational document and tends to be a new indexing named by “Relative Keyword Indexing”.

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Zhang, Qiong. "Hierarchical Route Representation, Indexing, and Search." IEEE Pervasive Computing 7, no. 2 (2008): 78–84. http://dx.doi.org/10.1109/mprv.2008.31.

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S., Priyanka, and Satish R. "Inverted Indexing Mechanism for Search Engine." International Journal of Computer Applications 123, no. 17 (2015): 15–19. http://dx.doi.org/10.5120/ijca2015905770.

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Duda, Cristian, Donald Kossmann, and Chong Zhou. "Predicate-based indexing for desktop search." VLDB Journal 19, no. 5 (2010): 735–58. http://dx.doi.org/10.1007/s00778-010-0187-5.

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Askin, Nicole, Tyler Ostapyk, and Carla Epp. "Filtering failure: the impact of automated indexing in Medline on retrieval of human studies for knowledge synthesis." Journal of the Medical Library Association 113, no. 1 (2025): 58–64. https://doi.org/10.5195/jmla.2025.1972.

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Objective: Use of the search filter ‘exp animals/ not humans.sh’ is a well-established method in evidence synthesis to exclude non-human studies. However, the shift to automated indexing of Medline records has raised concerns about the use of subject-heading-based search techniques. We sought to determine how often this string inappropriately excludes human studies among automated as compared to manually indexed records in Ovid Medline. Methods: We searched Ovid Medline for studies published in 2021 and 2022 using the Cochrane Highly Sensitive Search Strategy for randomized trials. We identifi

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Khodiakova, Halyna V., Nataliia V. Khodiakova, and Valery A. Pozdeev. "Full Text Search Setup on a Website." Control Systems and Computers, no. 5-6 (295-296) (December 2021): 55–60. http://dx.doi.org/10.15407/csc.2021.05-06.055.

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ntroduction. When implementing the search for text fragments on the site, approaches are used that are different in complexity and performance. There is also a sequence of related tasks: choosing a text indexing option, sending a text for indexing, selecting texts for indexing specifically from the CMS database, choosing a search engine, and others. These approaches do not always provide satisfactory search results. Purpose. The purpose of the article is to the description of existing solutions for full-text search on a website, their advantages, and disadvantages. Development of a full-text s

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Dissertations / Theses on the topic "Search Indexing"

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Graves, Andrew Phillip. "Iconic indexing for video search." Thesis, Queen Mary, University of London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440504.

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Reimers, Axel, and Isak Gustafsson. "Indexing and Search Algorithmsfor Web shops :." Thesis, KTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-193373.

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Web shops today needs to be more and more responsive, where one part of this responsivenessis fast product searches. One way of getting faster searches are by searching against anindex instead of directly against a database. Network Expertise Sweden AB (Net Exp) wants to explore different methods of implementingan index in their future web shop, building upon the open-source web shop platformSmartStore.NET. Since SmartStore.NET does all of its searches directly against itsdatabase, it will not scale well and will wear more on the database. The aim was thereforeto find different solutions to of

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Leon, Barth Carlos. "Phoneme-based video indexing using phonetic disparity search." Doctoral diss., University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4628.

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This dissertation presents and evaluates a method to the video indexing problem by investigating a categorization method that transcribes audio content through Automatic Speech Recognition (ASR) combined with Dynamic Contextualization (DC), Phonetic Disparity Search (PDS) and Metaphone indexation. The suggested approach applies genome pattern matching algorithms with computational summarization to build a database infrastructure that provides an indexed summary of the original audio content. PDS complements the contextual phoneme indexing approach by optimizing topic seek performance and accur

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Mergen, Sérgio Luis Sardi. "Indexing and querying dataspaces." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/31134.

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Over theWeb, distributed and heterogeneous sources with structured and related content form rich repositories of information commonly referred to as dataspaces. To provide access to this heterogeneous data, information integration systems have traditionally relied on the availability of a mediated schema, along with mappings between this schema and the schema of the source schemas. On dataspaces, where sources are plentiful, autonomous and extremely volatile, a system based on the existence of a pre-defined mediated schema and mapping information presents several drawbacks. Notably, the cost o

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Mbikiwa, Fernie Neo. "Search engine exclusion policies: implications on indexing e-commerce websites." Thesis, [S.l. : s.n.], 2005. http://dk.cput.ac.za/cgi/viewcontent.cgi?article=1080&context=td_cput.

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Potamias, Michalis. "Indexing Distances in Large Graphs and Applications in Search Tasks." Boston University Computer Science Department, 2009. https://hdl.handle.net/2144/1721.

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This thesis elaborates on the problem of preprocessing a large graph so that single-pair shortest-path queries can be answered quickly at runtime. Computing shortest paths is a well studied problem, but exact algorithms do not scale well to real-world huge graphs in applications that require very short response time. The focus is on approximate methods for distance estimation, in particular in landmarks-based distance indexing. This approach involves choosing some nodes as landmarks and computing (offline), for each node in the graph its embedding, i.e., the vector of its distances fr

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Peng, Botao. "Parrallel data series indexing and similarity search on modern hardware." Electronic Thesis or Diss., Université Paris Cité, 2020. http://www.theses.fr/2020UNIP5193.

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La recherche de similarité de séries de données est une opération essentielle pour plusieurs applications dans de nombreux domaines. Cependant, les techniques de pointe ne parviennent pas à fournir les performances temporelles requises, que ce soit pour réaliser une exploration interactive des séries de données, ou simplement une analyse de grandes collections de données. Au cours de ma thèse, nous présentons les premières solutions d'indexation de séries de données conçues pour tirer parti intrinsèquement du matériel moderne, afin d'accélérer les temps de traitement de la recherche de similar

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Costa, Miguel. "SIDRA: a Flexible Web Search System." Master's thesis, Department of Informatics, University of Lisbon, 2004. http://hdl.handle.net/10451/13914.

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Sidra is a new indexing, searching and ranking system for Web contents. It has a flexible, parallel, distributed and scalable architecture. Sidra maintains several data structures that provide multiple access methods to different data dimensions, giving it the capability to select results reflecting search contexts. Its design addresses current challenges of Web search engines: high performance, short searching and indexing times, good quality of results, scalability and high service availability

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Wang, Ben. "Efficient indexing structures for similarity search in content-based information retrieval." Thesis, University of Essex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438150.

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Polyakov, Serhiy. "Enhancing User Search Experience in Digital Libraries with Rotated Latent Semantic Indexing." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804881/.

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This study investigates a semi-automatic method for creation of topical labels representing the topical concepts in information objects. The method is called rotated latent semantic indexing (rLSI). rLSI has found application in text mining but has not been used for topical labels generation in digital libraries (DLs). The present study proposes a theoretical model and an evaluation framework which are based on the LSA theory of meaning and investigates rLSI in a DL environment. The proposed evaluation framework for rLSI topical labels is focused on human-information search behavior and satisf

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Books on the topic "Search Indexing"

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G, Gosling Carolyn, Knight Nancy H, McKenney Linda S, and American Psychological Association, eds. Search PsycINFO instructor guide. American Psychological Association, 1989.

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Susan, Esparza, and Clay, eds. Search Engine Optimization. For Dummies [Imprint], 2009.

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Toselli, Alejandro Héctor, Joan Puigcerver, and Enrique Vidal. Probabilistic Indexing for Information Search and Retrieval in Large Collections of Handwritten Text Images. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55389-9.

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Tisseghem, Patrick. Inside the index and search engines: Microsoft Office SharePoint server 2007. Microsoft Press, 2008.

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Services, PsycINFO User. Search PsycINFO: Student workbook. American Psychological Association, 1988.

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Konia, Brad S. Search engine optimization with WebPosition Gold 2. Wordware Pub., 2002.

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Clay, Bruce. Search engine optimization all-in-one for dummies. 2nd ed. John Wiley & Sons, 2012.

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Bergamin, Giovanni, Mauro Guerrini, and Carlotta Alpigiano, eds. Bibliographic Control in the Digital Ecosystem. Firenze University Press, 2022. http://dx.doi.org/10.36253/978-88-5518-544-8.

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With the contributions of international experts, the book aims to explore the new boundaries of universal bibliographic control. Bibliographic control is radically changing because the bibliographic universe is radically changing: resources, agents, technologies, standards and practices. Among the main topics addressed: library cooperation networks; legal deposit; national bibliographies; new tools and standards (IFLA LRM, RDA, BIBFRAME); authority control and new alliances (Wikidata, Wikibase, Identifiers); new ways of indexing resources (artificial intelligence); institutional repositories;

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Search Psycinfo/Instructor Guide. American Psychological Association (APA), 1989.

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Akdogan, Hüseyin. Elasticsearch Indexing: Improve Search Experiences with ElasticSearch's Powerful Indexing Functionality - Learn How with This Practical ElasticSearch Tutorial, Packed with Tips! Packt Publishing, Limited, 2015.

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Book chapters on the topic "Search Indexing"

1

Vlachos, Michail. "Indexing and Similarity Search." In Encyclopedia of Database Systems. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_615-2.

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Vlachos, Michail. "Indexing and Similarity Search." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_615.

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Toselli, Alejandro Héctor, Joan Puigcerver, and Enrique Vidal. "Probabilistic Indexing Search Extensions." In Probabilistic Indexing for Information Search and Retrieval in Large Collections of Handwritten Text Images. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55389-9_8.

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Vlachos, Michail. "Indexing and Similarity Search." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_615.

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Cambazoglu, B. Barla, and Ricardo Baeza-Yates. "The Indexing System." In Scalability Challenges in Web Search Engines. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-031-02298-2_3.

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P, Deepak, and Prasad M. Deshpande. "Indexing for Similarity Search Operators." In Operators for Similarity Search. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21257-9_6.

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Mohamed, Hisham, and Stéphane Marchand-Maillet. "Quantized Ranking for Permutation-Based Indexing." In Similarity Search and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41062-8_11.

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Bause, Franka, David B. Blumenthal, Erich Schubert, and Nils M. Kriege. "Metric Indexing for Graph Similarity Search." In Similarity Search and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89657-7_24.

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Lu, Jiaheng. "XML Data Indexing." 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_3.

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Razente, Humberto, Régis Michel Santos Sousa, and Maria Camila Nardini Barioni. "Metric Indexing Assisted by Short-Term Memories." In Similarity Search and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02224-2_9.

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Conference papers on the topic "Search Indexing"

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Kang, SeongKu, Yunyi Zhang, Pengcheng Jiang, Dongha Lee, Jiawei Han, and Hwanjo Yu. "Taxonomy-guided Semantic Indexing for Academic Paper Search." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.407.

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Pantelidis, Nick, Maria Pegia, Damianos Galanopoulos, et al. "Verge: Simplifying Video Search for Novice Users." In 2024 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2024. https://doi.org/10.1109/cbmi62980.2024.10859248.

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Luu, Duc-Tuan, Duy-Ngoc Nguyen, Khanh-Linh Bui-Le, Vinh-Tiep Nguyen, and Minh-Triet Tran. "IMSearch: An Interactive Multimedia Video-Moment Search System." In 2024 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2024. https://doi.org/10.1109/cbmi62980.2024.10859200.

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Khan, Omar Shahbaz, Ujjwal Sharma, Stevan Rudinac, and Björn Pór Jónsson. "Exquisitor: Studying the Interplay Between Conversational Search and Relevance Feedback." In 2024 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2024. https://doi.org/10.1109/cbmi62980.2024.10859234.

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Nixon, Lyndon, Damianos Galanopoulos, and Vasileios Mezaris. "Finding Video Shots for Immersive Journalism Through Text-to-Video Search." In 2024 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE, 2024. https://doi.org/10.1109/cbmi62980.2024.10859220.

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Figueroa, Karina, and Kimmo Frediksson. "Speeding Up Permutation Based Indexing with Indexing." In 2009 Second International Workshop on Similarity Search and Applications (SISAP). IEEE, 2009. http://dx.doi.org/10.1109/sisap.2009.12.

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Mika, Peter. "Distributed indexing for semantic search." In the 3rd International Semantic Search Workshop. ACM Press, 2010. http://dx.doi.org/10.1145/1863879.1863882.

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Arge, Lars. "Worst-case efficient range search indexing." In the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium. ACM Press, 2009. http://dx.doi.org/10.1145/1559795.1559822.

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Chen, Lu, Yunjun Gao, Xinhan Li, Christian S. Jensen, and Gang Chen. "Efficient metric indexing for similarity search." In 2015 IEEE 31st International Conference on Data Engineering (ICDE). IEEE, 2015. http://dx.doi.org/10.1109/icde.2015.7113317.

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Tian, Qi. "Session details: Multimedia Search and Indexing." In MM '14: 2014 ACM Multimedia Conference. ACM, 2014. http://dx.doi.org/10.1145/3246845.

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Reports on the topic "Search Indexing"

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Melnyk, Yuriy. Academic Journal Website Model. KRPOCH, 2018. http://dx.doi.org/10.26697/preprint.melnyk.1.2018.

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Background: The tens of thousands of academic journal websites that are on the Internet today often do not have a clear organizational structure for their website. If most of them are convenient enough for readers (if the journal is open access), then many have problems informing authors about the conditions, the process of submitting and reviewing the manuscript. The Editorial Offices empirically populate the journal's website with content that can change dramatically (both in terms of website design and content) as the journal develops. Aim of Study: To develop a website model for an academi

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Decleir, Cyril, Mohand-Saïd Hacid, and Jacques Kouloumdjian. A Database Approach for Modeling and Querying Video Data. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.90.

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Indexing video data is essential for providing content based access. In this paper, we consider how database technology can offer an integrated framework for modeling and querying video data. As many concerns in video (e.g., modeling and querying) are also found in databases, databases provide an interesting angle to attack many of the problems. From a video applications perspective, database systems provide a nice basis for future video systems. More generally, database research will provide solutions to many video issues even if these are partial or fragmented. From a database perspective, v

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