363,155 Hits in 3.3 sec

Using Machine Learning To Build A Search Engine

Priyanka R, Megha G S
2021 Zenodo  
Searching for information on the internet differs in several ways.  ...  Web pages.  ...  It only searches when a user asks a search engine for information, Journal of Advance Research in Mobile Computing Volume 3 Issue 2 not the entire internet.  ... 
doi:10.5281/zenodo.5215149 fatcat:7m27ljfdevf6tnoq5jg6kcizfm


Roopesh Kevin Sungkur, Ibne Raheeman, Yusrah Musbally
2016 IJAEDU- International E-Journal of Advances in Education  
The semantic web is an advancement of the current web that is being used, the web 2.0, which comprises mainly of metadata i.e. data about data.  ...  Information on the Web is commonly represented in natural-language for human understanding.  ...  Web 2.0 searches for pages; Web 3.0 searches for information.  ... 
doi:10.18768/ijaedu.01611 fatcat:jd5avltoerhxrm3zi3j67f6xwq

Extracting search-focused key n-grams for relevance ranking in web search

Chen Wang, Keping Bi, Yunhua Hu, Hang Li, Guihong Cao
2012 Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12  
We address the challenge by learning a model that can extract search-focused key n-grams from web pages, and using the key n-grams for searches of the pages, particularly, the tail pages.  ...  In web search, relevance ranking of popular pages is relatively easy, because of the inclusion of strong signals such as anchor text and search log data.  ...  We take search log data as training data for learning the model of extraction (one can also consider taking anchor text data as training data).  ... 
doi:10.1145/2124295.2124338 dblp:conf/wsdm/WangBHLC12 fatcat:q6og47faizchfmmfghkjfvsmqu

Enhanced Model to Improve Memory Based Learning Algorithm

Aastha Gupta
2014 IOSR Journal of Computer Engineering  
Thus, this algorithm is ineffective, when dealing with sparse data. To be able to deal with this limitation, we have devised an enhanced Memory Based Learning model.  ...  Learning Algorithm.  ...  Enhanced Model to Improve Memory Based Learning Algorithm  ... 
doi:10.9790/0661-16686168 fatcat:kytzveuakfduxb4rcudtyud44u

Effects of student characteristics and question design on Internet search results usage in a Taiwanese classroom

Chuen-Tsai Sun, Shu-Hao Ye, Hsi-Chien Hsieh
2014 Computers & Education  
All of the participants were experienced in using computers, the Web, and search engines.  ...  Longer and more indepth searches require critical analyses of results as part of a process that is thought to produce better learning outcomes.  ...  Acknowledgments The authors thank the blind reviewers of this paper for their insightful and constructive comments. They are grateful for helpful input on paper organization from Jon Lindemann.  ... 
doi:10.1016/j.compedu.2014.04.020 fatcat:nnhojqpolnhufmbtjb5wblqoxi

Webly Supervised Learning for Skin Lesion Classification [article]

Fernando Navarro, Sailesh Conjeti, Federico Tombari, Nassir Navab
2018 arXiv   pre-print
To improve the representativeness of the training dataset, for the first time, we present an approach to utilize large amounts of freely available web data through web-crawling.  ...  We also leverage search by image to improve the search specificity of our web-crawling and reduce cross-domain noise.  ...  The proposed noise correction approach by modeling cross-category noise helps in learning an effective network initialization from web data.  ... 
arXiv:1804.00177v1 fatcat:kzwnbyrbcjbldlshe4aucngt7u

A Web Mining Approach for Personalized E-Learning System

Manasi Chakurkar, Prof.Deepa Adiga
2014 International Journal of Advanced Computer Science and Applications  
The Web Mining plays a very important role for the E-learning systems. In personalized E-Learning system, user customize the learning environment based on personal choices.  ...  For making a personalized system history of every user need to be saved in the form of user logs. In this paper we present a architecture with the use of Web mining for Web personalization.  ...  As shown in Fig. 6 , when users search for java keyword, he gets different links.  ... 
doi:10.14569/ijacsa.2014.050306 fatcat:uqq3vk252rh3xbrur5xbk3hkh4

Detecting online commercial intention (OCI)

Honghua (Kathy) Dai, Lingzhi Zhao, Zaiqing Nie, Ji-Rong Wen, Lee Wang, Ying Li
2006 Proceedings of the 15th international conference on World Wide Web - WWW '06  
We train machine learning models from two types of data sources for a given search query: content of algorithmic search result page(s) and contents of top sites returned by a search engine.  ...  Previous work on Web search defines three major types of user search goals for search queries: navigational, informational and transactional or resource [1] [7] .  ...  ACKNOWLEDGMENTS Our thanks to MSN [16] for allowing us to access the search data.  ... 
doi:10.1145/1135777.1135902 dblp:conf/www/DaiZNWWL06 fatcat:wfitarcn4bhkbku3pj4hr5w45q

Self-study in learning foreign language

D Dauletova, G Dauletbaeva
2022 Ренессанс в парадигме новаций образования и технологий в XXI веке  
The use of technology has received increasing recognition as a means capable of bridging formal and informal settings in the target language learning and enabling students to actively and effectively use  ...  the web for information, listening to the radio, exploring cultural knowledge on YouTube and so on.  ...  data on students' language learning strategies, which was based on the classification of the language learning strategies.  ... 
doi:10.47689/innovations-in-edu-vol-iss1-pp191-193 fatcat:tonl3kicszdqrnp54zer4hbz4m

Effective Search Engine Spam Classification

2019 International journal of recent technology and engineering  
Search engine spam is formed by the spam creators for commercial gain. Spammers applied different strategies in web pages to display the first page of web search results.  ...  Even though search engines are still affected by search engine spam. There is a necessity for search engine industry to filter search engine spam in the best way.  ...  Numerous machine learning algorithms are applied to classification task. Machine learning method is better than other methods for classifying search engine spam [8, 9] .  ... 
doi:10.35940/ijrte.b1100.0882s819 fatcat:zotzmascpnakvjpf4jedk23eri

Service identification using k-NN machine learning

Travis Joseph Poulose, S Ganesh Kumar
2018 International Journal of Engineering & Technology  
With the help of machine learning we can also predict the user's service request automatically based on previous searches and also select the best web service for a particular request that the user has  ...  Semantic based service descriptions is necessary for accurate web categorization.  ...  A Concept Search is when we try to search these web services based on the semantic representation of them.  ... 
doi:10.14419/ijet.v7i2.4.13035 fatcat:uql4ajozabcehl6l7jdtji4n2q

Framework for Distributed e-Learning Management System

Thongchai Kaewkiriya, Ryosuke Saga, Hiroshi Tsuji
2013 Journal of Computers  
The prototype of distributed e-learning management system is also designed by REST (Representational State Transferred) ful web services.  ...  Based on functional role and system flow, this paper designs user interface framework for teacher, students and administrator.  ...  Mauricio LETELIER for checking the draft.  ... 
doi:10.4304/jcp.8.7.1635-1647 fatcat:ulmbe46vfzd35iym2hfzmgzgpa

Personalized information retrieval in digital ecosystems

Dengya Zhu, Heinz Dreher
2008 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies  
In this paper, a personalized information retrieval paradigm is proposed which not only implicitly creates user profile by learning users' search history, search preferences, and desktop information by  ...  By comparing the cosine similarities between vectors represent personal valued search concepts in user profiles, and vectors represent search concepts in the retrieved search results, the search results  ...  However, as pointed out by [30] , the following four issues need to be considered when using machine learning algorithms for user modelling, that is, the need for large data sets, the need for labelled  ... 
doi:10.1109/dest.2008.4635207 fatcat:hxxva4g2jbhyjmgwdphomfyigi

Extending a Web Browser with Client-Side Mining [chapter]

Hongjun Lu, Qiong Luo, Yeuk Kiu Shun
2003 Lecture Notes in Computer Science  
WBext learns sophisticated user interests and browsing habits by tailoring and integrating data mining techniques including association rules mining, clustering, and text mining, to suit the web browser  ...  We present WBext (Web Browser extended), a web browser extended with client-side mining capabilities.  ...  Moreover, they only track link following and web page visits as the raw data for learning tasks.  ... 
doi:10.1007/3-540-36901-5_18 fatcat:ybk4t2w4wbbzhawf54buguopfe

Developing Distributed Repositories of Learning Objects [chapter]

Salvador Otn, Antonio Ortiz, Luis de-Marcos, Sergio Mazo de Dios, Antonio Garca, Eva Garca, Jos R., Roberto Barchino
2012 Methodologies, Tools and New Developments for E-Learning  
When exchanging data, semantic interoperability is achieved when data is interpreted in the same way by all the applications involved.  ...  ); content portals (for an instance: searching systems of digital libraries, World Wide Web searching, etc.); or any application/software developed to access to learning objects.  ... 
doi:10.5772/29447 fatcat:5wsgv2l7sffuheileali3pfz4e
« Previous Showing results 1 — 15 out of 363,155 results