Titlebook: Web Technologies and Applications; 13th Asia-Pacific We Xiaoyong Du,Wenfei Fan,Mohamed A. Sharaf Conference proceedings 2011 Springer Berli

象形文字

Cleaning Uncertain Streams for Query Improvement, application context covers specific cleaning rules to bring data close to the reality (i.e. data quality), and query features can filter data for the efficiency (i.e. data volume). In this paper, we propose a framework for cleaning uncertain data for query effectiveness and efficiency, which proce

先兆

anarchist

Personalized Web Search with User Geographic and Temporal Preferencesation needs. We propose a novel approach to capture user’s geographic and temporal preferences in the form of . and . by mining search results and user click-through data leveraging knowledge bases. Our approach classifies queries into five classes based on decision tree algorithm. When personalizin

etidronate

Cleaning Uncertain Streams for Query Improvement, application context covers specific cleaning rules to bring data close to the reality (i.e. data quality), and query features can filter data for the efficiency (i.e. data volume). In this paper, we propose a framework for cleaning uncertain data for query effectiveness and efficiency, which proce

不可知论

Web User Profiling on Proxy Logs and Its Evaluation in Personalization words represent users and their actions. The main technical challenge addressed here is how to symbolize web access actions, by words, that are monitored through a web proxy. We develop a hierarchical URL dictionary generated from Yahoo! Directory and a cross-hierarchical matching method that provi

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刻苦读书

褪色

Atrium

Exploring Folksonomy and Cooking Procedures to Boost Cooking Recipe Recommendationtrieval despite the explosive data growth. Similar to other popular domains such as the movie-, music-, and book- recommendations, cooking recipe selection is also a daily activity in which user experiences can be greatly improved by adopting appropriate recommendation strategies. Based on content-b

减弱不好

Effective Hybrid Recommendation Combining Users-Searches Correlations Using Tensorsmensional models to find inter relationships between alike users and products. This paper proposes a novel recommendation method using the multi-dimensional model, tensor, to group similar users based on common search behaviour, and then finding associations within such groups for making effective i