Lightweight Distributed Trust Propagation Export

@proceedings{citeulike:2986523, abstract = {Using mobile devices, such as smart phones, people may create and distribute different types of digital content (e.g., photos, videos). One of the problems is that digital content, being easy to create and replicate, may likely swamp users rather than informing them. To avoid that, users may organize content producers that they know and trust in a web of trust. Users may then reason about this web of trust to form opinions about content producers with whom they have never interacted before. These opinions will then determine whether content is accepted. The process of forming opinions is called trust propagation. We design a mechanism for mobile devices that effectively propagates trust and that is lightweight and distributed (as opposed to previous work that focuses on centralized propagation). This mechanism uses a graph-based learning technique. We evaluate the effectiveness (predictive accuracy) of this mechanism against a large real-world data set. We also evaluate the computational cost of a J2ME implementation on a mobile phone.}, author = {Quercia, D. and Hailes, S. and Capra, L.}, booktitle = {Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on}, citeulike-article-id = {2986523}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICDM.2007.64}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4470252}, doi = {10.1109/ICDM.2007.64}, journal = {Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on}, keywords = {mobile, propagation, trust}, pages = {282--291}, posted-at = {2009-01-03 16:42:35}, priority = {2}, title = {Lightweight Distributed Trust Propagation}, url = {http://dx.doi.org/10.1109/ICDM.2007.64}, year = {2007} }

TY - CONF ID - citeulike:2986523 L3 - citeulike-article-id:2986523 N2 - Using mobile devices, such as smart phones, people may create and distribute different types of digital content (e.g., photos, videos). One of the problems is that digital content, being easy to create and replicate, may likely swamp users rather than informing them. To avoid that, users may organize content producers that they know and trust in a web of trust. Users may then reason about this web of trust to form opinions about content producers with whom they have never interacted before. These opinions will then determine whether content is accepted. The process of forming opinions is called trust propagation. We design a mechanism for mobile devices that effectively propagates trust and that is lightweight and distributed (as opposed to previous work that focuses on centralized propagation). This mechanism uses a graph-based learning technique. We evaluate the effectiveness (predictive accuracy) of this mechanism against a large real-world data set. We also evaluate the computational cost of a J2ME implementation on a mobile phone. JF - Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on EP - 291 TI - Lightweight Distributed Trust Propagation T2 - Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on SP - 282 KW - mobile KW - propagation KW - trust AU - Quercia, D AU - Hailes, S AU - Capra, L PY - 2007/// UR - http://dx.doi.org/10.1109/ICDM.2007.64 ER -