Matches in ScholarlyData for { ?s ?p ?o. }
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- item-1 hasContent qiaozhu-mei.
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- item-2 hasContent deng-cai.
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- item-3 hasContent duo-zhang.
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- item-4 hasContent chengxiang-zhai.
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- 810 creator jonathan-koren.
- 810 creator xue-liu.
- 810 creator yi-zhang.
- 810 type InProceedings.
- 810 label "Personalized Interactive Faceted Search".
- 810 sameAs 810.
- 810 abstract "Faceted search interfaces are becoming a popular method to allow users to interactively search and navigate complex information spaces. These interfaces present users with key-value metadata that is used in query refinement. While popular in e-commerce and digital libraries, not much research has been conducted on which metadata to present to a user in order to improve the search experience, nor are there repeatable benchmarks to use when evaluating a faceted search interface. We propose using collaborative filtering and personalization to customize the search interface to each user's behavior. We also propose a utility based framework to evaluate the faceted interface. A set of three algorithms for generating a faceted search interface are proposed and evaluated using the novel evaluation methodology.".
- 810 hasAuthorList authorList.
- 810 hasTopic World_Wide_Web.
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- 810 keyword "collaborative recommendation".
- 810 keyword "faceted search".
- 810 keyword "interactive search".
- 810 keyword "personalization".
- 810 keyword "user modeling".
- 810 title "Personalized Interactive Faceted Search".
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- item-1 hasContent jonathan-koren.
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- item-2 hasContent yi-zhang.
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- item-3 hasContent xue-liu.
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- 813 creator anton-riabov.
- 813 creator eric-bouillet.
- 813 creator zhen-liu.
- 813 type InProceedings.
- 813 label "Wishful Search: Interactive Composition of Data Mashups".
- 813 sameAs 813.
- 813 abstract "With the emergence of Yahoo Pipes and several similar services, data mashup tools have started to gain interest of business users. Making these tools simple and accessible to users with no or little programming experience has become a pressing issue. In this paper we introduce MARIO (Mashup Automation with Runtime Orchestration and Invocation), a new tool that radically simplifies data mashup composition. We have developed an intelligent automatic composition engine in MARIO together with a simple user interface using an intuitive “wishful search” abstraction. It thus allows users to explore the space of potentially composable data mashups and preview composition results as they iteratively refine their “wishes”, i.e. mashup composition goals. It also lets users discover and make use of system capabilities without having to understand the capabilities of individual components, and instantly reflects changes made to the components by presenting an aggregate view of changed capabilities of the entire system. We describe our experience with using MARIO to compose flows of Yahoo Pipes components.".
- 813 hasAuthorList authorList.
- 813 hasTopic World_Wide_Web.
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- 813 keyword "composition".
- 813 keyword "consumability".
- 813 keyword "mashup".
- 813 keyword "programmable web".
- 813 keyword "tag clouds".
- 813 title "Wishful Search: Interactive Composition of Data Mashups".
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- item-1 hasContent anton-riabov.
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- item-2 hasContent eric-bouillet.
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- item-3 hasContent zhen-liu.
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- 819 creator jason-hartline.
- 819 creator mukund-sundararajan.
- 819 creator vahab-mirrokni.
- 819 type InProceedings.
- 819 label "Optimal Marketing Strategies over Social Networks".
- 819 sameAs 819.
- 819 abstract "We discuss the use of social networks in implementing viral marketing strategies. While \emph{influence maximization} has been studied in this context(see Chapter 24 of ~\cite{AGTBook}), we study \emph{revenue maximization}, arguably, a more natural objective. In our model, a buyer's decision to buy an item is based both which other buyers own the item and the price at which the item is offered. When the buyers are completely symmetric, we can find the optimal marketing strategy in polynomial time. In the general case, motivated by hardness results, we investigate approximation algorithms for this problem. We identify a class of strategies called \emph{influence-and-exploit strategies} that are based on the following idea: Initially \emph{influence} the population by giving the item for free to carefully chosen set of buyers. Then extract revenue from the remaining buyers using a `greedy' pricing strategy. We first argue why such strategies are reasonable and then show how to use recently developed set-function maximization techniques to find the right set of buyers to influence.".
- 819 hasAuthorList authorList.
- 819 hasTopic World_Wide_Web.
- 819 isPartOf proceedings.
- 819 keyword "Monetizing Social Networks".
- 819 keyword "Pricing".
- 819 keyword "Submodular Maximization".
- 819 keyword "combinatorial optimization".
- 819 keyword "viral Marketing".
- 819 title "Optimal Marketing Strategies over Social Networks".
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