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1

Buxton, Stephen. "Beyond Search: Content Applications." IT Professional 9, no. 1 (2007): 29–35. http://dx.doi.org/10.1109/mitp.2007.4.

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Chutel, Pushpa, Titiksha Bhagat, Snehal Dongre, and Sonam Chopade. "Content Based Reverse Image Search." SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology 14, no. 01 SPL (2022): 1–5. http://dx.doi.org/10.18090/samriddhi.v14spli01.1.

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People can now get access to the required image with a relevant degree of information thanks to the broad improvement of the WWW. Details, photos, flow charts, logos, maps, and other information However, discovering and obtaining relevant information is always a challenge. There are certain text-based search engines, such as Google, that may be used to find desired photographs from the vast pool of images available on the internet. As a result, here need for the pictures online search engine that can search for related and proper images. Content-based image retrieval query approach is same as Reverse image search that involves giving the CBIR device an example photo and having it find photos based on that image. Reverse image search mostly used to find out either information or photos linked to the query image, as well as accurate images.
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3

Lu, Jian, Xian-Sheng Hua, and Dong Xu. "Visual Content Identification and Search." IEEE Multimedia 18, no. 3 (2011): 8–10. http://dx.doi.org/10.1109/mmul.2011.52.

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4

Rodrigues, Erick O., Panos Liatsis, Luiz Satoru, and Aura Conci. "Fractal triangular search: a metaheuristic for image content search." IET Image Processing 12, no. 8 (2018): 1475–84. http://dx.doi.org/10.1049/iet-ipr.2017.0790.

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Ti, Haowei, and Ding Ma. "Research on Google Search and Amazon Search Based on the Comparison of Algorithms." International Journal of Economics & Management Sciences 11, no. 3 (2022): 4. https://doi.org/10.37421/ 2162-6359.2022.11.626.

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Search engine optimization, which can optimize the search display position of content and expose the target content to readers faster, is a great tool for marketing. For foreign trade practitioners, the traffic entrances of the two major search engines, Amazon and Google, determine the exposure of products. Amazon drives consumers to click and search with shopping as the demand and has a clearer consumption intention, while Google is a bigger information plaza than Amazon, leading people to various websites.
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6

Davidavičius, Sigitas. "Peculiarities of online user’s content search in the context of inbound marketing." Business: Theory and Practice 25, no. 2 (2024): 502–8. http://dx.doi.org/10.3846/btp.2024.17177.

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The article addresses the issue of the distribution of users browsing the internet for content in a specific format through alternative content delivery channels in the context of inbound marketing. The problem being addressed is part of a broader problem with the formation of traffic to an organization’s website. The theoretical part of the work presents the concept of inbound marketing and analyzes the theoretical aspects of its tactical activities, such as content marketing, search engine marketing, and social media marketing. Based on the theoretical research, the scientific hypothesis is formulated – there are links between the desired content format and the choice of content search and consumption channel. The research methodology consists of data collection by survey method and hypothesis testing using Cochran’s Q test. Empirical research has shown links between the content format sought and the channels for searching and consuming content. Although in almost all cases the search for video and audio content is dominated by search engines, evaluating other content delivery channels reveals a significant specialty of users’ web browsing.
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Abel, Fabian, Matteo Baldoni, Cristina Baroglio, et al. "Leveraging search and content exploration by exploiting context in folksonomy systems." New Review of Hypermedia and Multimedia 16, no. 1-2 (2010): 33–70. http://dx.doi.org/10.1080/13614568.2010.497193.

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8

Ma, Xiao Xing, and Di Wu. "Content-Based Multimedia Files Search Technology." Applied Mechanics and Materials 644-650 (September 2014): 1895–98. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1895.

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At present, digital multimedia files containing text, images, audio and video are four main formats. In the search for multimedia files, because dissemination of images, audio and video files on the Internet, is lack of uniform standards, the same content will be used to describe different keywords. And it contains the richer content, the larger the amount of file data, as thus the traditional theme keyword search technology cannot meet the needs of the way of images and audio and video files. Text search technology is the most mature and widely used. Content-based search engine of search technology is an important topic in the development of digital media files on Internet search.
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9

Shelke, Sonali K. "Web Content Extractor for Privacy Search." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 5 (2017): 312–16. http://dx.doi.org/10.23956/ijarcsse/v7i5/0133.

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10

Lopatin, D. V., E. S. Chirkin, and A. A. Fadeeva. "PHONETIC SEARCH ALGORITHM OF INAPPROPRIATE CONTENT." Tambov University Reports. Series: Natural and Technical Sciences 22, no. 5-2 (2017): 1138–41. http://dx.doi.org/10.20310/1810-0198-2017-22-5-1138-1141.

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11

Fouad, Mohamed M. "Content-based Search for Image Retrieval." International Journal of Image, Graphics and Signal Processing 5, no. 11 (2013): 46–52. http://dx.doi.org/10.5815/ijigsp.2013.11.05.

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12

Repovienė, Rūta. "Content Marketing Elements for Search Advertising." Socialiniai tyrimai 40, no. 1 (2017): 47–54. http://dx.doi.org/10.21277/st.v40i1.184.

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The author analyzes the possibility of using content marketing elements for search advertising from marketing experts and searchers’ perspective. The first part of the paper deals with the theoretical insights into the concepts of content marketing, search advertising, their effect and synergy. The second part is qualitative research on a theoretical model of content marketing elements. The possibility of using those elements and modifying the theoretical model are provided in the third part of the paper. Research results revealed that content marketing elements can be used for search advertising and that they affect search advertising. Conclusions and directions for further research. are provided in the paper.
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13

Wade, J. P., and C. G. Sodini. "A ternary content addressable search engine." IEEE Journal of Solid-State Circuits 24, no. 4 (1989): 1003–13. http://dx.doi.org/10.1109/4.34085.

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14

Church, Karen, and Barry Smyth. "Improving mobile search using content enrichment." Artificial Intelligence Review 28, no. 1 (2007): 87–102. http://dx.doi.org/10.1007/s10462-008-9073-6.

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15

White, Ryen W., and Ahmed Hassan. "Content Bias in Online Health Search." ACM Transactions on the Web 8, no. 4 (2014): 1–33. http://dx.doi.org/10.1145/2663355.

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16

Moustakas, Konstantinos, Georgios Nikolakis, Dimitrios Tzovaras, Sebastien Carbini, Olivier Bernier, and Jean Emmanuel Viallet. "3D content-based search using sketches." Personal and Ubiquitous Computing 13, no. 1 (2007): 59–67. http://dx.doi.org/10.1007/s00779-007-0166-z.

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17

Han, Yan. "Digital content management: the search for a content management system." Library Hi Tech 22, no. 4 (2004): 355–65. http://dx.doi.org/10.1108/07378830410570467.

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18

Jasmine K. S., Rishav Raj, and Mahalakshmi Mabla Naik. "A New Content-Based Search Mechanism for Image Retrieval Search Engine." International Journal of Information Retrieval Research 12, no. 1 (2022): 1–16. http://dx.doi.org/10.4018/ijirr.289611.

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In the growing world of technology, where everything is available in just one click, the user expectations has increased with time. In the era of Search Engines, where Google, Yahoo are providing the facility to search through text and voice and image , it has become a complex work to handle all the operations and lot more of data storage is needed. It is also a time consuming process. In the proposed Image retrieval Search Engine, the user enters the queried image and that image is being matched with the template images . The proposed approach takes the input image with 15% accuracy to 100% accuracy to retrieve the intended image by the user. But it is found that due to the efficiency of the applied algorithm, in all cases, the retrieved images are with the same accuracy irrespective of the input query image accuracy. This implementation is very much useful in the fields of forensic, defense and diagnostics system in medical field etc. .
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SCHIESSL, Marcelo, and Marisa BRÄSCHER. "Ontology lexicalization: Relationship between content and meaning in the context of Information Retrieval." Transinformação 29, no. 1 (2017): 57–72. http://dx.doi.org/10.1590/2318-08892017000100006.

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Abstract The proposal presented in this study seeks to properly represent natural language to ontologies and vice-versa. Therefore, the semi-automatic creation of a lexical database in Brazilian Portuguese containing morphological, syntactic, and semantic information that can be read by machines was proposed, allowing the link between structured and unstructured data and its integration into an information retrieval model to improve precision. The results obtained demonstrated that the methodology can be used in the risco financeiro (financial risk) domain in Portuguese for the construction of an ontology and the lexical-semantic database and the proposal of a semantic information retrieval model. In order to evaluate the performance of the proposed model, documents containing the main definitions of the financial risk domain were selected and indexed with and without semantic annotation. To enable the comparison between the approaches, two databases were created based on the texts with the semantic annotations to represent the semantic search. The first one represents the traditional search and the second contained the index built based on the texts with the semantic annotations to represent the semantic search. The evaluation of the proposal was based on recall and precision. The queries submitted to the model showed that the semantic search outperforms the traditional search and validates the methodology used. Although more complex, the procedure proposed can be used in all kinds of domains.
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20

Rifiana, Arief, Widodo Suryarini, Bima Kurniawan Ary, Hustinawaty, and Arkan Faisal. "Advanced content-based retrieval for digital correspondence documents with ontology classification." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1665~1677. https://doi.org/10.11591/eei.v11i3.3376.

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The growth of digital correspondence documents with various types, different naming rules, and no sufficient search system complicates the search process with certain content, especially if there are unclassified documents, the search becomes inaccurate and takes a long time. This research proposed archiving method with automatic hierarchical classification and the content-based search method which displays ontology classification information as the solution to the content-based search problems. The method consists of preprocessing (creation of automatic hierarchical classification model using a combination of convolutional neural network (CNN) and regular expression method), archiving (document archiving with automatic classification), and retrieval (content-based search by displaying ontology relationships from the document classification). The archiving of 100 documents using the automatic hierarchical classification was found to be 79% accurate as indicated by the 99% accuracy for CNN and 80% for Regex. Moreover, the search results for classified content-based documents through the display of ontology relationships were discovered to be 100% accurate. This research succeeded in improving the quality of search results for digital correspondence documents as indicated by its higher specificity, accuracy, and speed compared to conventional methods based on file names, annotations, and unclassified content.
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21

Katz, Elihu. "Ownership, Technology, Content, and Context in the Continuing Search for Media Effects." Annals of the International Communication Association 35, no. 1 (2011): 1–11. http://dx.doi.org/10.1080/23808985.2011.11679108.

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22

De Vocht, Laurens, Selver Softic, Ruben Verborgh, Erik Mannens, and Martin Ebner. "Social Semantic Search." International Journal on Semantic Web and Information Systems 13, no. 4 (2017): 155–80. http://dx.doi.org/10.4018/ijswis.2017100108.

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When researchers formulate search queries to find relevant content on the Web, those queries typically consist of keywords that can only be matched in the content or its metadata. The Web of Data extends this functionality by bringing structure and giving well-defined meaning to the content and it enables humans and machines to work together using controlled vocabularies. Due the high degree of mismatches between the structure of the content and the vocabularies in different sources, searching over multiple heterogeneous repositories of structured data is considered challenging. Therefore, the authors present a semantic search engine for researchers facilitating search in research related Linked Data. To facilitate high-precision interactive search, they annotated and interlinked structured research data with ontologies from various repositories in an effective semantic model. Furthermore, the authors' system is adaptive as researchers can synchronize using new social media accounts and efficiently explore new datasets.
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23

Mat Husain, Mohd Pirdaus, Ali Salman, Mohd Nor Shahizan Ali, and Khairunnisa Mohad Khazin. "Newcomers in politics: A thematic analysis of 2023 Malaysian State Election candidates’ TikTok content." SEARCH Journal Media and Communication Research 16, no. 2 (2024): 83–100. http://dx.doi.org/10.58946/search-16.2.p6.

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In Malaysia, the 2023 State Election was held on August 12, 2023. This election only involved six states, namely Selangor, Kedah, Kelantan, Terengganu, Negeri Sembilan, and Penang. It also had a large number of candidates from different backgrounds. Among them were new candidates nominated by their respective parties. New candidates are also known as a “political newcomers”. These newcomers were of various backgrounds, including artists, athletes, entrepreneurs, and academicians. All of them presented distinctive manifestos and viewpoints that was shared on social media. In this context, this research aims to examine the content uploaded by four different newcomers in their personal social media account, which is TikTok. A total of 173 uploaded contents were analysed utilising descriptive analysis and thematic analysis. Based on the analysis, six different themes emerged reflecting the political newcomers’ background including education, social welfare, economy, health and sports, corruption, and safety/security. Three major themes: education, social welfare, and health & sports stood out as the most significant and relevant to research objectives, highlighting the issues that resonate most with voters. The study underscores the significance of social media, particularly TikTok, as a powerful tool for disseminating content on critical national issues. By focusing on education, social welfare, and health & sports, political newcomers tapped into the concerns and aspirations of the electorate, in the hopes of gaining their support and eventual votes.
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24

Kurokawa, Takeru, and Naohiro Hayashibara. "Content placement using Cuckoo search in Cloud-based Content delivery networks." Internet of Things 16 (December 2021): 100430. http://dx.doi.org/10.1016/j.iot.2021.100430.

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25

Pao, Hsiao, and Hsin Fu. "Content-based Search for Effective Image Retrieval." International Conference on Electrical Engineering 7, no. 7 (2010): 1–10. http://dx.doi.org/10.21608/iceeng.2010.33291.

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26

Kavitha, V. "Content Search Control for Named Data Networking." International Journal of Communication and Networking System 5, no. 2 (2016): 123–25. http://dx.doi.org/10.20894/ijcnes.103.005.002.007.

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Takegawa, Kazuki, Yoshinori Hijikata, and Shogo Nishida. "Content-based Music Search and Recommendation System." Transactions of the Japanese Society for Artificial Intelligence 23 (2008): 330–43. http://dx.doi.org/10.1527/tjsai.23.330.

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28

Yang Li. "Gesture Search: Random Access to Smartphone Content." IEEE Pervasive Computing 11, no. 1 (2012): 10–13. http://dx.doi.org/10.1109/mprv.2012.9.

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29

Swan, Kathy, and Mark Hofer. "In Search of Technological Pedagogical Content Knowledge." Journal of Research on Technology in Education 44, no. 1 (2011): 75–98. http://dx.doi.org/10.1080/15391523.2011.10782580.

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30

McCreadie, Richard. "News vertical search using user-generated content." ACM SIGIR Forum 47, no. 1 (2013): 62–63. http://dx.doi.org/10.1145/2492189.2492202.

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31

Nordström, Erik, Christian Rohner, and Per Gunningberg. "Haggle: Opportunistic mobile content sharing using search." Computer Communications 48 (July 2014): 121–32. http://dx.doi.org/10.1016/j.comcom.2014.03.017.

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32

Zhou, Zhengzhong, and Liqing Zhang. "Content-Based Image Retrieval Using Iterative Search." Neural Processing Letters 47, no. 3 (2017): 907–19. http://dx.doi.org/10.1007/s11063-017-9662-y.

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Merabti, Madjid, Zhu Liu, Heather Yu, and Deepa Kundur. "Advances In Peer-To-Peer Content Search." Journal of Signal Processing Systems 59, no. 3 (2009): 309–18. http://dx.doi.org/10.1007/s11265-009-0343-6.

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34

N., Vanashri. "A Survey on Personalized Multimedia Content Search." International Journal on Recent and Innovation Trends in Computing and Communication 3, no. 2 (2015): 629–32. http://dx.doi.org/10.17762/ijritcc2321-8169.150243.

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35

Kim, Ki-Young, Yu-Hwa Suh, and Byung-Joon Park. "User control based OTT content search algorithms." Journal of the Korea Society of Computer and Information 20, no. 5 (2015): 99–106. http://dx.doi.org/10.9708/jksci.2015.20.5.099.

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36

Kim, Byung-Gon, and Sung-Kyun Oh. "Content based data search using semantic annotation." Journal of Digital Contents Society 12, no. 4 (2011): 429–36. http://dx.doi.org/10.9728/dcs.2011.12.4.429.

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37

Rathishbabu, TKS, V. Anantha Krishna, M. Ramasubramanian, and V. Balaji. "Mining Specific Content Search using Clustering Algorithm." Journal of Physics: Conference Series 1228 (May 2019): 012057. http://dx.doi.org/10.1088/1742-6596/1228/1/012057.

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38

Stone, Harold S., and Talal G. Shamoon. "Search-by-content of partially occluded images." International Journal on Digital Libraries 1, no. 4 (1998): 329–43. http://dx.doi.org/10.1007/s007990050027.

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39

Urman, Aleksandra, Aniko Hannak, and Mykola Makhortykh. "User Attitudes to Content Moderation in Web Search." Proceedings of the ACM on Human-Computer Interaction 8, CSCW1 (2024): 1–27. http://dx.doi.org/10.1145/3637423.

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Internet users highly rely on and trust web search engines, such as Google, to find relevant information online. However, scholars have documented numerous biases and inaccuracies in search outputs. To improve the quality of search results, search engines employ various content moderation practices such as interface elements informing users about potentially dangerous websites and algorithmic mechanisms for downgrading or removing low-quality search results. While the reliance of the public on web search engines and their use of moderation practices is well-established, user attitudes towards these practices have not yet been explored in detail. To address this gap, we first conducted an overview of content moderation practices used by search engines, and then surveyed a representative sample of the US adult population (N=398) to examine the levels of support for different moderation practices applied to potentially misleading and/or potentially offensive content in web search. We also analyzed the relationship between user characteristics and their support for specific moderation practices. We find that the most supported practice is informing users about potentially misleading or offensive content, and the least supported one is the complete removal of search results. More conservative users and users with lower levels of trust in web search results are more likely to be against content moderation in web search.
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Wu, Xiao, Chong-Wah Ngo, Alexander G. Hauptmann, and Hung-Khoon Tan. "Real-Time Near-Duplicate Elimination for Web Video Search With Content and Context." IEEE Transactions on Multimedia 11, no. 2 (2009): 196–207. http://dx.doi.org/10.1109/tmm.2008.2009673.

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41

Pereira, E., and M. Castelhano. "Guidance during Visual Search in Real-World Scenes: Scene Context vs. Object Content." Journal of Vision 11, no. 11 (2011): 1320. http://dx.doi.org/10.1167/11.11.1320.

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42

Iwata, Mayu, Hiroki Miyamoto, Takahiro Hara, et al. "A content search system considering the activity and context of a mobile user." Personal and Ubiquitous Computing 17, no. 5 (2012): 1035–50. http://dx.doi.org/10.1007/s00779-012-0550-1.

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43

Szűcs, Gábor, and Dávid Papp. "Content-Based Image Retrieval for Multiple Objects Search." Cybernetics and Information Technologies 17, no. 2 (2017): 106–18. http://dx.doi.org/10.1515/cait-2017-0020.

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Abstract The progress of image search engines still proceeds, but there are some challenges yet in complex queries. In this paper, we present a new semantic image search system, which is capable of multiple object retrieval using only visual content of the images. We have used the state-of-the-art image processing methods prior to the search, such as Fisher-vector and C-SVC classifier, in order to semantically classify images containing multiple objects. The results of this offline classification are stored for the latter search task. We have elaborated more search methods for combining the results of binary classifiers of objects in images. Our search methods use confidence values of object classifiers and after the evaluation, the best method is selected for thorough analysis. Our solution is compared with the famous web images search engines (Google, Bing and Flickr), and there is a comparison of their Mean Average Precision (MAP) values. It can be concluded that our system reaches the benchmark; moreover, in most cases our method outperforms the others, especially in the cases of queries with many objects.
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44

Gradmann, Stefan. "From containers to content to context." Journal of Documentation 70, no. 2 (2014): 241–60. http://dx.doi.org/10.1108/jd-05-2013-0058.

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Purpose – The aim of this paper is to reposition the research library in the context of the changing information and knowledge architecture at the end of the “Gutenberg Parenthesis” and as part of the rapidly emerging “semantic” environment of the Linked Open Data paradigm. Understanding this process requires a good understanding of the evolution of the “document” notion in the passage from print based culture to the distributed hypertextual and RDF based information architecture of the WWW. Design/methodology/approach – These objectives are reached using literature study and a descriptive historical approach as well as text mining techniques using Google nGrams as a data source. Findings – The paper presents a proposal for effectively repositioning research libraries in the context of eScience and eScholarship as well as clear indications of the proposed repositioning already taking place. Furthermore, a new perspective of the “document” notion is provided. Practical implications – The evolution described in the contribution creates opportunities for libraries to reposition themselves as aggregators and selectors of content and as contextualising agents as part of future Linked Data based scholarly research environments provided they are able and ready to operate the related cultural changes. Originality/value – The paper will be useful for practitioners in search of strategic guidance for repositioning their librarian institutions in a context of ever increasing competition for scarce funding resources.
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Eberli, D., A. Bachmann, J. Konetschny, T. Gasser, and T. Sulser. "Search strategies for the internet: Introducing the first search engine for urologic content." European Urology Supplements 2, no. 1 (2003): 201. http://dx.doi.org/10.1016/s1569-9056(03)80798-4.

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46

Prò, Luzmila, Carlos Yañez, and Juan Carlos Gonzales. "SPATIAL SEARCH." Revista de investigación de Sistemas e Informática 2, no. 2 (2005): 78–82. http://dx.doi.org/10.15381/risi.v2i2.3221.

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The spatial search, is an type of search local with internet, which local search to locate into an area of space o distance an specific center of reference, at this type search with point reference known geospatial proximity searching (1). The data base requires for this search preparing of data in several steps: The first step is to locate text that the application geographic can be map for the phisical location, this step, is easily for aplications of the directory as equal the yellow pages for internet, in this caseas this conformated of a structure simple of data base with defined maenings for each field. For Intenet derived the content the problem is complex because the text wirth geographic significance can be anywhere on a page. The second step is referent at the transform location of the textual designation into the physical coordinates on the earth´s surface, in order for the detection geographicof the content in the text of the documents, sidebar describes, topic of the detectinggeographic into the text documents has generated interest of business and the investigation (7).
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47

Liapis, Antonios, Georgios N. Yannakakis, and Julian Togelius. "Constrained Novelty Search: A Study on Game Content Generation." Evolutionary Computation 23, no. 1 (2015): 101–29. http://dx.doi.org/10.1162/evco_a_00123.

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Novelty search is a recent algorithm geared toward exploring search spaces without regard to objectives. When the presence of constraints divides a search space into feasible space and infeasible space, interesting implications arise regarding how novelty search explores such spaces. This paper elaborates on the problem of constrained novelty search and proposes two novelty search algorithms which search within both the feasible and the infeasible space. Inspired by the FI-2pop genetic algorithm, both algorithms maintain and evolve two separate populations, one with feasible and one with infeasible individuals, while each population can use its own selection method. The proposed algorithms are applied to the problem of generating diverse but playable game levels, which is representative of the larger problem of procedural game content generation. Results show that the two-population constrained novelty search methods can create, under certain conditions, larger and more diverse sets of feasible game levels than current methods of novelty search, whether constrained or unconstrained. However, the best algorithm is contingent on the particularities of the search space and the genetic operators used. Additionally, the proposed enhancement of offspring boosting is shown to enhance performance in all cases of two-population novelty search.
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48

Ziegler, Wolfgang. "Semantic Correlation Rules as a Logic Layer between Content Management and Content Delivery." SHS Web of Conferences 102 (2021): 02007. http://dx.doi.org/10.1051/shsconf/202110202007.

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Semantic technologies have recently gained considerable influence and attention in the field of technical communication and information management. While metadata management is already a well-known field of content management technologies, its semantic extension addresses more recently, for example, problems of model-based product development and related content engineering processes. On the other hand, dynamic search technology and content delivery can benefit from semantic modelling by enhancing search functionalities or by integrating various data sources utilizing semantic mapping. In this evolving environment, we propose a logical layer of content correlations as so-called semantic correlation rules (SCR). This layer can be understood as an interface between content management systems, semantic modelling systems and content delivery portals. Semantic correlation rules serve as a light-weight ontology consisting primarily of untyped semantic relations between metadata classes. In doing so, class-to-class linking mechanisms can be implemented in content delivery and search environments while serving as a basis for the previously introduced microDoc concept
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49

Kwak, Dong-Won, Kyoung-Soo Bok, Tae-Ho Kang, Myung-Ho Yeo, Jae-Soo Yoo, and Ki-Hung Joe. "Efficient Mobile P2P Structure for Content Search Services." Journal of the Korea Contents Association 9, no. 1 (2009): 30–44. http://dx.doi.org/10.5392/jkca.2009.9.1.030.

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Rats, Juris, and Gints Ernestsons. "Clustering and Ranked Search for Enterprise Content Management." International Journal of E-Entrepreneurship and Innovation 4, no. 4 (2013): 20–31. http://dx.doi.org/10.4018/ijeei.2013100102.

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Abstract:
The aim of this work is to understand more closely where the border lies between relational and Not Only Structured Query Language (NoSQL) platform as concerns Enterprise Content Management (ECM) area. Another objective (closely related to the first one) is to specify the conceptual architecture of the distributed ECM system. The authors specify the model of the prototype ECM system and compare two platforms for this model – MS SQL based for the relational platform and Clusterpoint for the NoSQL platform. The results of performance measurements of SQL and NoSQL technologies for Enterprise Content Management specific tasks are presented and analyzed. The viability of NoSQL Document-oriented database solution based on clustering and ranked search is demonstrated. The ways to leverage the improved performance and scalability of the software to better serve the business needs of the Enterprise are discussed. The conceptual architecture of the prototype system is outlined.
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