Gotowe bibliografie tematyczne / Personalized Web search

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Gotowa bibliografia na temat „Personalized Web search”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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Artykuły w czasopismach na temat "Personalized Web search"

Choi, Dae Young. "Towards Location-Based Personalized Voice Web Search on SmartphonesTowards Location-Based Personalized Voice Web Search on Smartphones." Journal of Computers 11, no. 1 (2016): 62–71. http://dx.doi.org/10.17706/jcp.11.1.62-71.

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Sukanya, L., and R. Vijaya. "A Framework for Privacy-Enhancing Personalized Web Search." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 2698–701. http://dx.doi.org/10.31142/ijtsrd12885.

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Roy T P, Roy T. P., and Ginnu George. "A Novel Personalized Web Search with Offline Capability." International Journal of Scientific Research 3, no. 5 (2012): 243–45. http://dx.doi.org/10.15373/22778179/may2014/73.

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Nidhi, Saxena, and Gupta Bineet. "Personalized Web Search Architecture Supporting Privacy." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 3351–57. https://doi.org/10.35940/ijeat.C5953.029320.

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Web is gigantic wellspring of information and data and each one relies upon it for accomplishing all kind of information. With the presence of enormous information and assortment of data it gets hard for end client to separate required data. Thus there comes the need to customize every client search so as to acquire important outcomes at the time of searching. This paper gives architecture of internet search utilizing an improved customized method which recognizes every client search keeping protection as a measure concern. The proposed plan is more valuable where more than one client get to s

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Gupta, Disha, and Nekita Chavhan. "Personalized Mobile Web Search Techniques." International Journal of Scientific and Engineering Research 4, no. 11 (2014): 1193–98. http://dx.doi.org/10.14299/ijser.2013.11.001.

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FAUZIA, PARVEEN M.F.RAHMAN, and CHOLE VIKRANT. "VOICE ENABLE PERSONALIZED WEB SEARCH." JournalNX - a Multidisciplinary Peer Reviewed Journal 3, no. 6 (2017): 38–41. https://doi.org/10.5281/zenodo.1421019.

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The technology of voice browsing is rapidly evolving these days. It is because the use of cell phones is increasing at a very high rate, as compared to connected PCs. Speech interface integrated browser is a web browser that helps users by using an interactive voice user interface ,useful to those who have difficulties in seeing and reading a web content. Listening and speaking are the natural modes of communication and information gathering. As a result we are now heading towards a more voice based approach of browsing rather than operating on textual mode. A voice browser or speech browser w

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M Durugkar, Sneha, and Saudagar S Barde. "Privacy Protection in Personalized Web Search Using Metric Prediction." International Journal of Scientific Engineering and Research 3, no. 9 (2015): 65–68. https://doi.org/10.70729/ijser15467.

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Tamboli, Najneen, and Sathish Kumar Penchala. "User Profile Based Personalized Web Search." International Journal of Managing Public Sector Information and Communication Technologies 7, no. 3 (2016): 15–22. http://dx.doi.org/10.5121/ijmpict.2016.7302.

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Kim, Je-Min, and Young-Tack Park. "Personalized Search Service in Semantic Web." KIPS Transactions:PartB 13B, no. 5 (2006): 533–40. http://dx.doi.org/10.3745/kipstb.2006.13b.5.533.

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Volkovich, Yana, and Nelly Litvak. "Asymptotic analysis for personalized Web search." Advances in Applied Probability 42, no. 2 (2010): 577–604. http://dx.doi.org/10.1239/aap/1275055243.

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PageRank with personalization is used in Web search as an importance measure for Web documents. The goal of this paper is to characterize the tail behavior of the PageRank distribution in the Web and other complex networks characterized by power laws. To this end, we model the PageRank as a solution of a stochastic equationwhere theRis are distributed asR. This equation is inspired by the original definition of the PageRank. In particular,Nmodels the number of incoming links to a page, andBstays for the user preference. Assuming thatNorBare heavy tailed, we employ the theory of regular variati

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Rozprawy doktorskie na temat "Personalized Web search"

Jiang, Hao, and 江浩. "Personalized web search re-ranking and content recommendation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/197548.

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In this thesis, I propose a method for establishing a personalized recommendation system for re-ranking web search results and recommending web contents. The method is based on personal reading interest which can be reflected by the user’s dwell time on each document or webpage. I acquire document-level dwell times via a customized web browser, or a mobile device. To obtain better precision, I also explore the possibility of tracking gaze position and facial expression, from which I can determine the attractiveness of different parts of a document. Inspired by idea of Google Knowledge Graph

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Crain, Steven P. "Personalized search and recommendation for health information resources." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45805.

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Consumers face several challenges using the Internet to fill health-related needs. (1) In many cases, they face a language gap as they look for information that is written in unfamiliar technical language. (2) Medical information in social media is of variable quality and may be appealing even when it is dangerous. (3) Discussion groups provide valuable social support for necessary lifestyle changes, but are variable in their levels of activity. (4) Finding less popular groups is tedious. We present solutions to these challenges. We use a novel adaptation of topic models to address the langua

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Gnasa, Melanie. "Congenial Web search a conceptual framework for personalized, collaborative, and social peer-to-peer retrieval /." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=981698069.

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Limbu, Dilip Kumar. "Contextual information retrieval from the WWW." Click here to access this resource online, 2008. http://hdl.handle.net/10292/450.

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Contextual information retrieval (CIR) is a critical technique for today’s search engines in terms of facilitating queries and returning relevant information. Despite its importance, little progress has been made in its application, due to the difficulty of capturing and representing contextual information about users. This thesis details the development and evaluation of the contextual SERL search, designed to tackle some of the challenges associated with CIR from the World Wide Web. The contextual SERL search utilises a rich contextual model that exploits implicit and explicit data to modify

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Tifrea-Marciuska, Oana. "Personalised search for the Social Semantic Web." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:27bda5a8-2360-46ad-bcef-e72ae1ae6f52.

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Recently, the Web has been changing more and more to what is called the Social Semantic Web. As a consequence, the ranking of search results no longer depends solely on the structure of the interconnections among Web pages. In my research, I argue that such ranking can be based on user preferences from the Social Web, and on ontological background knowledge from the Semantic Web. Therefore, I combine preference representation languages with Semantic Web technologies. There is some related research in database community that had dedicated some time to integrate preferences in database queries.

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Tanudjaja, Francisco 1978. "Using web graph structures to personalize search." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86737.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001. Includes bibliographical references (p. 93-97). by Francisco Tanudjaja. M.Eng.

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Gopinathan-Leela, Ligon, and n/a. "Personalisation of web information search: an agent based approach." University of Canberra. Information Sciences & Engineering, 2005. http://erl.canberra.edu.au./public/adt-AUC20060728.120849.

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The main purpose of this research is to find an effective way to personalise information searching on the Internet using middleware search agents, namely, Personalised Search Agents (PSA). The PSA acts between users and search engines, and applies new and existing techniques to mine and exploit relevant and personalised information for users. Much research has already been done in developing personalising filters, as a middleware technique which can act between user and search engines to deliver more personalised results. These personalising filters, apply one or more of the popular techniques

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Seyedarabi, Faezeh. "Developing a model of teachers' web-based information searching : a study of search options and features to support personalised educational resource discovery." Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/10018062/.

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This study has investigated the search options and features teachers use and prefer to have, when personalising their online search for teaching resources. This study focused on making web searching easier for UK teacher practitioners at primary, secondary and post-compulsory levels. In this study, a triangulated mixed method approach was carried out in a two phase iterative case study involving 75 teacher practitioners working in the UK educational setting. In this case study, a sequential evidence gathering method called ‘System Development Life Cycle’ (SDLC) was adapted linking findings obt

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Tsai, Jui-yu, and 蔡叡渝. "Personalized Web Search based on User’s Preference." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/aqk298.

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碩士 國立臺灣科技大學 資訊管理系 94 Web search engines help users find useful information on the World Wide Web (WWW). However, they are usually designed to serve all users, without considering the preference of individual users. The results returned from search engines are peppered with many impertinent data under most situations, and therefore users must pay a lot of effort to filter information. On the contrary, personalized web search provides customized results depending on each user’s preference, which can save a lot of time for users. In the thesis, we propose a method for personalizing we

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Huang, Fu-Kuang, and 黃復光. "A Personalized Intelligent Search Engine Integrator on the Web." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/68683855388220767236.

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Książki na temat "Personalized Web search"

Numerical Algorithms For Personalized Search In Selforganizing Information Networks. Princeton University Press, 2010.

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The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think. Penguin Books, 2012.

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Kant, Tanya. Making it Personal. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190905088.001.0001.

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The encounter of “personalized experiences”—targeted advertisements, tailored information feeds, and “recommended” content, among other things—is now a common and somewhat inescapable component of digital life. More often than not however, “you” the user are not primarily responsible for personalizing your web engagements: instead, with the help of your search, browsing, and purchase histories, your “likes,” your click-throughs, and a multitude of other data you produce as you go about your day, your experience can “conveniently”—and computationally—be personalized on your behalf. This book ex

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Merino Orozco, Abel, Cristina Di Giusto Valle, Gloria Pérez de Albéniz Garrote, and Valeriana Guijo Blanco. Education for fighting against gender discrimination and violence in the immigrant population: a systematic literature review. Universidad de Burgos, 2022. http://dx.doi.org/10.36443/9788418465284.

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Migrant women are exposed to double vulnerability, as women and as migrants. This generates a demand for special personalized attention from professionals in the social, health and psychology fields in order to understand their needs. This work aims to understand the complexity of the migratory phenomenon in women in the scientific literature to establish the priority lines of support in university curricula. For this, a systematic review is presented that finally analyzes 63 documents. The study has three search phases in Web of Science and Scopus databases. In the first phase, the terms that

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Volk, Hans-Dieter, and Levent Akyüz. Immunotherapy in critical illness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0055.

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Immunotherapy in critically-ill patients is only feasible at clinical experimental level; no therapy has been approved so far. To develop a potential therapeutic strategy we need to know the pathogen, immune status of the patient, and interaction between the particular pathogen and immune cells to readjust the patient´s individually imbalanced immunological responsiveness. Giving the right treatment at the right time is crucial for a better outcome and the best economic use of resources. The process starts by matching the therapeutic selection to the clinical need. Personalized immunotherapy,

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Sangeetha, V., and S. Kevin Andrews. Introduction to Artificial Intelligence and Neural Networks. Magestic Technology Solutions (P) Ltd, Chennai, Tamil Nadu, India, 2023. http://dx.doi.org/10.47716/mts/978-93-92090-24-0.

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Artificial Intelligence (AI) has emerged as a defining force in the current era, shaping the contours of technology and deeply permeating our everyday lives. From autonomous vehicles to predictive analytics and personalized recommendations, AI continues to revolutionize various facets of human existence, progressively becoming the invisible hand guiding our decisions. Simultaneously, its growing influence necessitates the need for a nuanced understanding of AI, thereby providing the impetus for this book, “Introduction to Artificial Intelligence and Neural Networks.” This book aims to equip it

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Części książek na temat "Personalized Web search"

Wen, Ji-Rong, Zhicheng Dou, and Ruihua Song. "Personalized Web Search." In Encyclopedia of Database Systems. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_267-2.

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Wen, Ji-Rong, Zhicheng Dou, and Ruihua Song. "Personalized Web Search." In Encyclopedia of Database Systems. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_267.

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Desu, Hema Sai, Phalani Paladugu, Santoshi Sameera Adibhatla, Sushma Swaroopa Sorda, and K. S. Sudeep. "Personalized Web Search." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1483-8_18.

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Wen, Ji-Rong, Zhicheng Dou, and Ruihua Song. "Personalized Web Search." In Encyclopedia of Database Systems. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_267.

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Lee, Hyun Chul, and Allan Borodin. "Cluster Based Personalized Search." In Algorithms and Models for the Web-Graph. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-95995-3_14.

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Zhang, Jianwei, Katsutoshi Minami, Yukiko Kawai, Yuhki Shiraishi, and Tadahiko Kumamoto. "Personalized Web Search Using Emotional Features." In Availability, Reliability, and Security in Information Systems and HCI. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40511-2_6.

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Biancalana, Claudio. "Social Tagging for Personalized Web Search." In AI*IA 2009: Emergent Perspectives in Artificial Intelligence. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10291-2_24.

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Wu, Yanping, Jun Zhao, Renjie Sun, Chen Chen, and Xiaoyang Wang. "Efficient Personalized Influential Community Search in Large Networks." In Web and Big Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60259-8_7.

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Vishnupriya, S., B. Selvaambigai, and S. Vigneshwari. "Supporting Privacy Protection in Personalized Web Search." In Advances in Power Systems and Energy Management. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7504-4_56.

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Yang, Dan, Tiezheng Nie, Derong Shen, Ge Yu, and Yue Kou. "Personalized Web Search with User Geographic and Temporal Preferences." In Web Technologies and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20291-9_12.

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Streszczenia konferencji na temat "Personalized Web search"

Jeh, Glen, and Jennifer Widom. "Scaling personalized web search." In the twelfth international conference. ACM Press, 2003. http://dx.doi.org/10.1145/775152.775191.

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Shafiq, Omair, Reda Alhajj, and Jon G. Rokne. "Community Aware Personalized Web Search." In 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2010). IEEE, 2010. http://dx.doi.org/10.1109/asonam.2010.85.

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Xu, Yabo, Ke Wang, Benyu Zhang, and Zheng Chen. "Privacy-enhancing personalized web search." In the 16th international conference. ACM Press, 2007. http://dx.doi.org/10.1145/1242572.1242652.

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Aslanyan, Grigor, Aritra Mandal, Prathyusha Senthil Kumar, Amit Jaiswal, and Manojkumar Rangasamy Kannadasan. "Personalized Ranking in eCommerce Search." In WWW '20: The Web Conference 2020. ACM, 2020. http://dx.doi.org/10.1145/3366424.3382715.

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Xu, Jingqiu, Zhengyu Zhu, Xiang Ren, Yunyan Tian, and Ying Luo. "Personalized Web Search Using User Profile." In 2007 International Conference on Computational Intelligence and Security (CIS 2007). IEEE, 2007. http://dx.doi.org/10.1109/cis.2007.167.

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Leung, Kenneth Wai-Ting, Dik Lun Lee, and Wang-Chien Lee. "Personalized Web search with location preferences." In 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icde.2010.5447911.

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Sendhilkumar, S., and T. V. Geetha. "Personalized ontology for web search personalization." In the 1st Bangalore annual Compute conference. ACM Press, 2008. http://dx.doi.org/10.1145/1341771.1341790.

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Liang, Chunyan. "User profile for personalized web search." In 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2011). IEEE, 2011. http://dx.doi.org/10.1109/fskd.2011.6019913.

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Jing, Kunlei, Fei Hao, Xizi Zhang, and Yu Zhou. "Personalized Semantic Matching for Web Search." In 2023 IEEE 39th International Conference on Data Engineering Workshops (ICDEW). IEEE, 2023. http://dx.doi.org/10.1109/icdew58674.2023.00037.

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"A PERSONALIZED INFORMATION SEARCH ASSISTANT." In 6th International Conference on Web Information Systems and Technologies. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002793200290039.

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Raporty organizacyjne na temat "Personalized Web search"

Arteaga, Felipe, Gregory Elacqua, Thomas Krussig, Carolina Méndez, and Christopher Neilson. Can Information on School Attributes and Placement Probabilities Direct Search and Choice? Evidence from Choice Platforms in Ecuador and Peru. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004672.

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This paper evaluates how new information influences families applica- tions and assignment outcomes in elementary school choice settings. Specifi- cally, using a multi-country RCT based in Tacna, Peru and Manta, Ecuador, we examine the effect of providing personalized information on schooling alternatives and placement risk. We find that applicants who received feed- back on placement risk and a suggestion of new schools add more schools to their applications and were more likely to include recommended schools than other alternatives available. Interestingly, the project implemented in Manta,

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