The Experts below are selected from a list of 22464 Experts worldwide ranked by ideXlab platform

L.-s. Chen - One of the best experts on this subject based on the ideXlab platform.

  • Personalization technology application to Internet Content Provider
    Expert Systems with Applications, 2001
    Co-Authors: Ying-feng Kuo, L.-s. Chen
    Abstract:

    Abstract Personalization of Web pages relates closely to targeting the customer and increasing customer intimacy thereby leading to increased branding and, hopefully, consumer electronic commerce. Profiling individuals on the Web allows us not only to select which message to deliver to each individual, but also helps us learn about the needs and interests of each person. In this paper, a modified tracking analysis method to obtain user preference inclination was proposed and applied to simulating ICP (Internet Content Provider) Web site. SNT (browsing sequence, node, and time) data extracted from the simulating Web site database are used extensively for our analysis. The ability to track user browsing behavior down to individual mouse clicks has brought the vendor and end customer closer than ever before.

Yukun Cao - One of the best experts on this subject based on the ideXlab platform.

  • application of a modified fuzzy art network to user classification for internet Content Provider
    Asia-Pacific Web Conference, 2006
    Co-Authors: Yukun Cao, Zhengyu Zhu, Chengliang Wang
    Abstract:

    Internet has entered the age led by ICP (Internet Content Provider). Helping users to locate relevant information in an efficient manner is very important both to users and to ICP services. This paper presents a new approach that employs a modified fuzzy ART network to group users dynamically based on their Web access patterns. Such a user clustering method should be performed prior to ICPs as the basis to provide personalized service. The experimental results of this clustering technique show the promise of our system.

  • APWeb Workshops - Application of a modified fuzzy ART network to user classification for internet Content Provider
    Lecture Notes in Computer Science, 2006
    Co-Authors: Yukun Cao, Zhengyu Zhu, Chengliang Wang
    Abstract:

    Internet has entered the age led by ICP (Internet Content Provider). Helping users to locate relevant information in an efficient manner is very important both to users and to ICP services. This paper presents a new approach that employs a modified fuzzy ART network to group users dynamically based on their Web access patterns. Such a user clustering method should be performed prior to ICPs as the basis to provide personalized service. The experimental results of this clustering technique show the promise of our system.

  • a user classification for internet Content Provider based modified fuzzy neural network
    International Conference on Asian Digital Libraries, 2005
    Co-Authors: Yukun Cao
    Abstract:

    With the explosive growth of the Internet, it has entered the age led by ICP (internet Content Provider). Helping users to locate relevant information in an efficient manner is very important both do the person and to the ICPs. As such, it is highly desired to have a systematic system for extracting user features effectively, and subsequently, analyzing user orientations quantitatively. The experimental results of this clustering technique show the promise of our system. This paper presents a new approach that employs a modified fuzzy neural network based on adaptive resonance theory to group users dynamically based on their Web access patterns. Such a user clustering method should be performed prior to ICPs as the basis to provide personalized service. The experimental results of this clustering technique show the promise of our system. The scheme could be used in local data management application, digital library, and so on.

  • ICADL - A user classification for internet Content Provider based modified fuzzy neural network
    Digital Libraries: Implementing Strategies and Sharing Experiences, 2005
    Co-Authors: Yukun Cao
    Abstract:

    With the explosive growth of the Internet, it has entered the age led by ICP (internet Content Provider). Helping users to locate relevant information in an efficient manner is very important both do the person and to the ICPs. As such, it is highly desired to have a systematic system for extracting user features effectively, and subsequently, analyzing user orientations quantitatively. The experimental results of this clustering technique show the promise of our system. This paper presents a new approach that employs a modified fuzzy neural network based on adaptive resonance theory to group users dynamically based on their Web access patterns. Such a user clustering method should be performed prior to ICPs as the basis to provide personalized service. The experimental results of this clustering technique show the promise of our system. The scheme could be used in local data management application, digital library, and so on.

Chengliang Wang - One of the best experts on this subject based on the ideXlab platform.

Eitan Altman - One of the best experts on this subject based on the ideXlab platform.

  • A Stochastic Game Approach for Competition over Popularity in Social Networks
    Dynamic Games and Applications, 2013
    Co-Authors: Eitan Altman
    Abstract:

    The global Internet has enabled a massive access of internauts to Content. At the same time, it allowed individuals to use the Internet in order to distribute Content. When individuals pass through a Content Provider to distribute Contents, they can benefit from many tools that the Content Provider has in order to accelerate the dessimination of the Content. These include caching as well as recommendation systems. The Content Provider gives preferential treatment to individuals who pay for advertisement. In this paper, we study competition between several Contents, each characterized by some given potential popularity. We answer the question of when is it worthwhile to invest in advertisement as a function of the potential popularity of a Content as well as its competing Contents, who are faced with a similar question. We formulate the problem as a stochastic game with a finite state and action space and obtain the structure of the equilibria policy under a linear structure of the dissemination utility as well as on the advertisement costs. We then consider open loop control (no state information) and solve the game using a transformation into a differential game with a compact state space.

  • A model of network neutrality with usage-based prices
    Telecommunication Systems, 2013
    Co-Authors: Eitan Altman, George Kesidis, Pierre Bernhard, Stephane Caron, Julio Rojas-mora, Sulan Wong
    Abstract:

    Hahn and Wallsten [7] wrote that network neutrality "usually means that broadband service Providers charge consumers only once for Internet access, do not favor one Content Provider over another, and do not charge Content Providers for sending information over broadband lines to end users." In this paper we study the implications of non-neutral behaviors under a simple model of linear demand-response to usage-based prices. We take into account advertising revenues for the Content Provider and consider both cooperative and non-cooperative scenarios. In particular, we model the: impact of side-payments between service and Content Providers, consider an access Provider that offers multiple service classes, and model leader-follower (Stackelberg game) dynamics. We finally study the additional option for one Provider to determine the amount of side payment from the other Provider. We show that not only do the Content Provider and the internaut suffer, but also the Access Provider's performance degrades.

  • Game theoretic approaches for studying competition over popularity and over advertisement space in social networks
    2012
    Co-Authors: Eitan Altman
    Abstract:

    Various tools are available for increasing the speed of Content dissemination such as embeddings in some popular web pages, sharing in some other social networks, and advertisement. In particular, when individuals pass through a Content Provider to distribute Contents, they can benefit from tools such as recommendation systems. The Content Provider can give a preferential treatment to individuals who pay for advertisement. In this paper we study competition between several Contents, each characterized by some given potential popularity. We study competition through advertisements that are placed at the beginning of the dissemination of Contents. We answer the question of when is it worthwhile to invest in advertisement as a function of the potential popularity of a Content as well as its competing Contents. The competition between similar Contents (e.g. news channels) over a finite set of potential destinations. We then consider a second model in which there is also competition on advertisement space. We compute the equilibrium strategy and identify its structure and properties for each one of the situations

  • A model of network neutrality with usage-based prices
    Telecommunication Systems, 2011
    Co-Authors: Eitan Altman, George Kesidis, Pierre Bernhard, Stephane Caron, Julio Rojas-mora, Sulan Wong
    Abstract:

    Hahn and Wallsten (Econ. Voice 3(6):1---7, 2006) wrote that network neutrality "usually means that broadband service Providers charge consumers only once for Internet access, do not favor one Content Provider over another, and do not charge Content Providers for sending information over broadband lines to end users." In this paper we study the implications of non-neutral behaviors under a simple model of linear demand-response to usage-based prices. We take into account advertising revenues for the Content Provider and consider both cooperative and non-cooperative scenarios. In particular, we model the: impact of side-payments between service and Content Providers, consider an access Provider that offers multiple service classes, and model leader-follower (Stackelberg game) dynamics. We finally study the additional option for one Provider to determine the amount of side payment from the other Provider. We show that not only do the Content Provider and the internaut suffer, but also the Access Provider's performance degrades.

  • A Study of Non-neutral Networks with Usage-Based Prices
    2010
    Co-Authors: Eitan Altman, George Kesidis, Pierre Bernhard, Stephane Caron, Julio Rojas-mora, Sulan Wong
    Abstract:

    Hahn and Wallsten [1] wrote that network neutrality "usually means that broadband service Providers charge consumers only once for Internet access, do not favor one Content Provider over another, and do not charge Content Providers for sending information over broadband lines to end users." We study the implications of non-neutral behaviors under a simple model of linear demand-response to usage-based prices. We take into account advertising revenues for the Content Provider and consider both cooperative and non-cooperative scenarios. We show that by adding the option for one Provider to determine the amount of side payment from the other Provider, not only do the Content Provider and the internaut suffer, but also the Access Provider's performance degrades.

Hanchieh Chao - One of the best experts on this subject based on the ideXlab platform.

  • an efficient cache strategy in information centric networking vehicle to vehicle scenario
    IEEE Access, 2017
    Co-Authors: Weicheng Zhao, Yajuan Qin, Deyun Gao, Chuan Heng Foh, Hanchieh Chao
    Abstract:

    Information centric networking (ICN) has been recently proposed as a prominent solution for Content delivery in vehicular ad hoc networks. By caching the data packets in vehicular unused storage space, vehicles can obtain the replicate of Contents from other vehicles instead of original Content Provider, which reduces the access pressure of Content Provider and increases the response speed of Content request. In this paper, we propose a community similarity and population-based cache policy in an ICN vehicle-to-vehicle scenario. First, a dynamic probability caching scheme is designed by evaluating the community similarity and privacy rating of vehicles. Then, a caching vehicle selection method with hop numbers based on Content popularity is proposed to reduce the cache redundancy. Moreover, to lower the cache replacement overhead, we put forward a popularity prediction-based cooperative cache replacement mechanism, which predicts and ranks popular Content during a period of time. Simulation results show that the performance of our proposed mechanisms is greatly outstanding in reducing the average time delay and increasing the cache hit ratio and the cache hit distance.