scholarly journals Mining Users’ Preference Similarities in E-commerce Systems Based on Webpage Navigation Logs

2017 ◽  
Vol 12 (5) ◽  
pp. 661 ◽  
Author(s):  
Ping Li ◽  
Chunxue Wu ◽  
Shaozhong Zhang ◽  
Xinwu Yu ◽  
Haidong Zhong
Keyword(s):  
Detection Algorithm ◽  
User Preference ◽  
Personalized Recommendation ◽  
Web Browsing ◽  
Web Page ◽  
Calculation Algorithm ◽  
Two Factors ◽  
Discovery Method ◽  
Preference Discovery ◽  
The Web

Mining users’ preference patterns in e-commerce systems is a fertile area for a great many application directions, such as shopping intention analysis, prediction and personalized recommendation. The web page navigation logs contain much potentially useful information, and provide opportunities for understanding the correlation between users’ browsing patterns and what they want to buy. In this article, we propose a web browsing history mining based user preference discovery method for e-commerce systems. First of all, a user-browsing-history-hierarchical-presentationgraph to established to model the web browsing histories of an individual in common e-commerce systems, and secondly an interested web page detection algorithm is designed to extract users’ preference. Finally, a new method called UPSAWBH (User Preference Similarity Calculation Algorithm Based on Web Browsing History), which measure the level of users’ preference similarity on the basis of their web page click patterns, is put forward. In the proposed UPSAWBH, we take two factors into account: 1) the number of shared web page click sequence, and 2) the property of the clicked web page that reflects users’ shopping preference in e-commerce systems. We conduct experiments on real dataset, which is extracted from the server of our self-developed e-commerce system. The results indicate a good effectiveness of the proposed approach.

Web Page Ranking Algorithm Based on the Meta-Information

2014 ◽  
Vol 596 ◽  
pp. 292-296
Author(s):  
Xin Li Li
Keyword(s):  
Experimental Results ◽  
High Rank ◽  
Ranking Algorithm ◽  
Web Page ◽  
Page Ranking ◽  
Two Factors ◽  
Meta Information ◽  
The Web

PageRank algorithms only consider hyperlink information, without other page information such as page hits frequency, page update time and web page category. Therefore, the algorithms rank a lot of advertising pages and old pages pretty high and can’t meet the users' needs. This paper further studies the page meta-information such as category, page hits frequency and page update time. The Web page with high hits frequency and with smaller age should get a high rank, while the above two factors are more or less dependent on page category. Experimental results show that the algorithm has good results.

scholarly journals Personalized Recommendation Algorithm for Web Pages Based on Associ ation Rule Mining

2018 ◽  
Vol 173 ◽  
pp. 03020
Author(s):  
Lu Xing-Hua ◽  
Ye Wen-Quan ◽  
Liu Ming-Yuan
Keyword(s):  
User Satisfaction ◽  
Personalized Recommendation ◽  
Web Pages ◽  
Semantic Features ◽  
Web Page ◽  
Web Crawler ◽  
Rule Mining ◽  
Recommendation Algorithm ◽  
Browsing Behavior ◽  
The Web

In order to improve the user ' s ability to access websites and web pages, according to the interest preference of the user, the personalized recommendation design is carried out, and the personalized recommendation model for web page visit is established to meet the personalized interest demand of the user to browse the web page. A webpage personalized recommendation algorithm based on association rule mining is proposed. Based on the semantic features of web pages, user browsing behavior is calculated by similarity computation, and web crawler algorithm is constructed to extract the semantic features of web pages. The autocorrelation matching method is used to match the features of web page and user browsing behavior, and the association rules feature quantity of user browsing website behavior is mined. According to the semantic relevance and semantic information of web users to search words, fuzzy registration is taken, Web personalized recommendation is obtained to meet the needs of the users browse the web. The simulation results show that the method is accurate and user satisfaction is higher.

Web Page Adaptation and Presentation for Mobile Phones

2010 ◽  
pp. 240-262 ◽  
Author(s):  
Yuki Arase ◽  
Takahiro Hara ◽  
Shojiro Nishio
Keyword(s):  
Mobile Phones ◽  
Mobile Commerce ◽  
Web Pages ◽  
Web Browsing ◽  
Web Page ◽  
Mobile Web ◽  
Large Displays ◽  
Key Technologies ◽  
Getting Lost ◽  
The Web

According to the explosive growth of mobile phones, mobile Web has been a part of our life. People can access the Web with their mobile phones and obtain information anywhere and anytime. This trend will stimulate the coming of mobile commerce, where people look for and purchase products on the Web whenever they want. Mobile Web is one of the key technologies for mobile commerce. However, since mobile phones have to be handheld, their interface is strictly limited. Users have to browse large-sized Web pages designed for large displays with a small screen and poor input capability of mobile phones. Additionally, considering mobile users browse Web pages in various situations, users’ needs towards presentation functionalities may different depending on their browsing situations. To provide comfortable Web browsing experience under these constraints, we have proposed two systems for mobile phone users. One system provides various presentation functions for Web browsing so that users can select appropriate ones based on their browsing situations. The other system provides functions to navigate users within a Web page so that they can find the information of their interest without getting lost in the page. In this chapter, we briefly introduce designs of these systems and introduce results of user experiments, through which we show that our systems can reduce users’ burden on mobile Web by enabling to select appropriate presentation functions adapted to their situations and by navigating them on a large Web page with the entertaining interface.

Rough Web Intelligent Techniques for Page Recommendation

2013 ◽  
pp. 170-191
Author(s):  
H. Inbarani ◽  
K. Thangavel
Keyword(s):  
Recommender Systems ◽  
Web Applications ◽  
Predictive Accuracy ◽  
Relevant Information ◽  
User Preference ◽  
Data Sets ◽  
Web Page ◽  
Recent Developments ◽  
Access Patterns ◽  
The Web

Recommender systems represent a prominent class of personalized Web applications, which particularly focus on the user-dependent filtering and selection of relevant information. Recommender Systems have been a subject of extensive research in Artificial Intelligence over the last decade, but with today’s increasing number of e-commerce environments on the Web, the demand for new approaches to intelligent product recommendation is higher than ever. There are more online users, more online channels, more vendors, more products, and, most importantly, increasingly complex products and services. These recent developments in the area of recommender systems generated new demands, in particular with respect to interactivity, adaptivity, and user preference elicitation. These challenges, however, are also in the focus of general Web page recommendation research. The goal of this chapter is to develop robust techniques to model noisy data sets containing an unknown number of overlapping categories and apply them for Web personalization and mining. In this chapter, rough set-based clustering approaches are used to discover Web user access patterns, and these techniques compute a number of clusters automatically from the Web log data using statistical techniques. The suitability of rough clustering approaches for Web page recommendation are measured using predictive accuracy metrics.

New species list of plants and lichens of Russia for Turboveg for Windows

2020 ◽  
pp. 151-156
Author(s):  
A. P. Korablev ◽  
N. S. Liksakova ◽  
D. M. Mirin ◽  
D. G. Oreshkin ◽  
P. G. Efimov
Keyword(s):  
New Species ◽  
Vascular Plants ◽  
Russian Literature ◽  
Web Page ◽  
Species List ◽  
Internet Resources ◽  
The World ◽  
A New Species ◽  
The Web

A new species list of plants and lichens of Russia and neighboring countries has been developed for Turboveg for Windows, the program, intended for storage and management of phytosociological data (relevés), is widely used all around the world (Hennekens, Schaminée, 2001; Hennekens, 2015). The species list is built upon the database of the Russian website Plantarium (Plantarium…: [site]), which contains a species atlas and illustrated an online Handbook of plants and lichens. The nomenclature used on Plantarium was originally based on the following issues: vascular plants — S. K. Cherepanov (1995) with additions; mosses — «Flora of mosses of Russia» (Proect...: [site]); liverworts and hornworts — A. D. Potemkin and E. V. Sofronova (2009); lichens — «Spisok…» G. P. Urbanavichyus ed. (2010); other sources (Plantarium...: [site]). The new species list, currently the most comprehensive in Turboveg format for Russia, has 89 501 entries, including 4627 genus taxa compare to the old one with 32 020 entries (taxa) and only 253 synonyms. There are 84 805 species and subspecies taxa in the list, 37 760 (44.7 %) of which are accepted, while the others are synonyms. Their distribution by groups of organisms and divisions are shown in Table. A large number of synonyms in the new list and its adaptation to work with the Russian literature will greatly facilitate the entry of old relevé data. The ways of making new list, its structure as well as the possibilities of checking taxonomic lists on Internet resources are considered. The files of the species list for Turboveg 2 and Turboveg 3, the technique of associating existing databases with a new species list (in Russian) are available on the web page https://www.binran.ru/resursy/informatsionnyye-resursy/tekuschie-proekty/species_list_russia/.

Legal Protection of the Web Page as a Database

2009 ◽  
Author(s):  
Mirko Luca Lobina ◽  
Davide Mula
Keyword(s):  
Legal Protection ◽  
Web Page ◽  
The Web

scholarly journals A Sign of Things to Come: Predicting the Perception of Above-the-Fold Time in Web Browsing

2021 ◽  
Vol 13 (2) ◽  
pp. 50
Author(s):  
Hamed Z. Jahromi ◽  
Declan Delaney ◽  
Andrew Hines
Keyword(s):  
Web Application ◽  
Web Applications ◽  
State Of The Art ◽  
Influencing Factor ◽  
The State ◽  
Experimental Result ◽  
Web Page ◽  
To Come ◽  
Web Quality ◽  
The Web

Content is a key influencing factor in Web Quality of Experience (QoE) estimation. A web user’s satisfaction can be influenced by how long it takes to render and visualize the visible parts of the web page in the browser. This is referred to as the Above-the-fold (ATF) time. SpeedIndex (SI) has been widely used to estimate perceived web page loading speed of ATF content and a proxy metric for Web QoE estimation. Web application developers have been actively introducing innovative interactive features, such as animated and multimedia content, aiming to capture the users’ attention and improve the functionality and utility of the web applications. However, the literature shows that, for the websites with animated content, the estimated ATF time using the state-of-the-art metrics may not accurately match completed ATF time as perceived by users. This study introduces a new metric, Plausibly Complete Time (PCT), that estimates ATF time for a user’s perception of websites with and without animations. PCT can be integrated with SI and web QoE models. The accuracy of the proposed metric is evaluated based on two publicly available datasets. The proposed metric holds a high positive Spearman’s correlation (rs=0.89) with the Perceived ATF reported by the users for websites with and without animated content. This study demonstrates that using PCT as a KPI in QoE estimation models can improve the robustness of QoE estimation in comparison to using the state-of-the-art ATF time metric. Furthermore, experimental result showed that the estimation of SI using PCT improves the robustness of SI for websites with animated content. The PCT estimation allows web application designers to identify where poor design has significantly increased ATF time and refactor their implementation before it impacts end-user experience.

The Research of the Accessibility Website Design Based on Web Log Mining

2012 ◽  
Vol 241-244 ◽  
pp. 2779-2782
Author(s):  
Heng Yao Tang ◽  
Xiao Yan Zhan
Keyword(s):  
Website Design ◽  
Web Log Mining ◽  
Web Page ◽  
Web Log ◽  
User Interests ◽  
Mining Technique ◽  
Dynamic Web ◽  
Log Mining ◽  
The Web

On the problems existing in the realization of current accessibility website, we design a web designing architecture, using the web log mining technique to extract user interests and access priority sequence and adopting the dynamic web page information to fill the web page commonly used structure, realize the intelligent , personalized accessibility.

Hypermedia, Eternal Life, and the Impermanence Agent

Leonardo ◽  
1999 ◽  
Vol 32 (5) ◽  
pp. 353-358 ◽  
Author(s):  
Noah Wardrip-Fruin
Keyword(s):  
Eternal Life ◽  
The Internet ◽  
Web Browsing ◽  
Original Stories ◽  
Internet Archive ◽  
Vannevar Bush ◽  
The Web ◽  
Critical Project

We look to media as memory, and a place to memorialize, when we have lost. Hypermedia pioneers such as Ted Nelson and Vannevar Bush envisioned the ultimate media within the ultimate archive—with each element in continual flux, and with constant new addition. Dynamism without loss. Instead we have the Web, where “Not Found” is a daily message. Projects such as the Internet Archive and Afterlife dream of fixing this uncomfortable impermanence. Marketeers promise that agents (indentured information servants that may be the humans of About.com or the software of “Ask Jeeves”) will make the Web comfortable through filtering—hiding the impermanence and overwhelming profluence that the Web's dynamism produces. The Impermanence Agent—a programmatic, esthetic, and critical project created by the author, Brion Moss, a.c. chapman, and Duane Whitehurst— operates differently. It begins as a storytelling agent, telling stories of impermanence, stories of preservation, memorial stories. It monitors each user's Web browsing, and starts customizing its storytelling by weaving in images and texts that the user has pulled from the Web. In time, the original stories are lost. New stories, collaboratively created, have taken their place.

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