The Experts below are selected from a list of 3579 Experts worldwide ranked by ideXlab platform
Robert Hoch - One of the best experts on this subject based on the ideXlab platform.
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Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising
Data Mining and Knowledge Discovery, 2001Co-Authors: Mark Podlaseck, Edith Schonberg, Robert HochAbstract:Clickstreams are visitors' paths through a Web site. Analysis of clickstreams shows how a Web site is navigated and used by its visitors. Clickstream data of online stores contains information useful for understanding the effectiveness of marketing and merchandising efforts, such as how customers find the store, what products they see, and what products they purchase. In this paper, we present an interactive visualization system that provides users with greater abilities to interpret and explore clickstream data of online stores. This system visualizes the effectiveness of Web merchandising from two different points of view by using two different visualization techniques: visualization of sessions by using parallel coordinates and visualization of product performance by using starfield graphs. Furthermore, this system provides facilities for zooming, filtering, color-coding, Dynamic Querying and data sampling. It also provides summary information along with visualizations, and by maintaining a connection between visualizations and the source database, it Dynamically updates the summary information. To demonstrate how the presented visualization system provides capabilities for examining online store clickstreams, we present a series of parallel coordinates and starfield visualizations that display clickstream data from an operating online retail store. A framework for understanding Web merchandising is briefly explained. A set of metrics referred to as micro-conversion rates , which are defined for Web merchandising analysis in our previous work (Lee et al., Electronic Markets, 2000), is also explained and used for the visualizations of online store effectiveness.
Mohammad R. Hashemian - One of the best experts on this subject based on the ideXlab platform.
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Advanced Querying Features for Disease Surveillance Systems Advanced Querying Features for Disease Surveillance Systems
2016Co-Authors: Mohammad R. HashemianAbstract:Abstract: Most automated disease surveillance systems notify users of increases in the prevalence of reports in syndrome categories and allow users to view patient level data related to those increases. Occasionally, a more Dynamic level of control is required to properly detect an emerging disease in a community. Dynamic Querying features are invaluable when using existing surveillance systems to investigate outbreaks of newly emergent diseases or to identify cases of reportable diseases within data being captured for surveillance. The objective of the Advance Querying Tool (AQT) is to build a more flexible query interface for most web-based disease surveillance systems. This interface allows users to define and build their query as if they were writing a logical expression for a mathematical computation. The AQT allows users to develop, investigate, save, and share complex case definitions. It provides a flexible interface that accommodates both advanced and novice users, checks the validity of the expression as it is built, and marks errors for users
Mark Podlaseck - One of the best experts on this subject based on the ideXlab platform.
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Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising
Data Mining and Knowledge Discovery, 2001Co-Authors: Mark Podlaseck, Edith Schonberg, Robert HochAbstract:Clickstreams are visitors' paths through a Web site. Analysis of clickstreams shows how a Web site is navigated and used by its visitors. Clickstream data of online stores contains information useful for understanding the effectiveness of marketing and merchandising efforts, such as how customers find the store, what products they see, and what products they purchase. In this paper, we present an interactive visualization system that provides users with greater abilities to interpret and explore clickstream data of online stores. This system visualizes the effectiveness of Web merchandising from two different points of view by using two different visualization techniques: visualization of sessions by using parallel coordinates and visualization of product performance by using starfield graphs. Furthermore, this system provides facilities for zooming, filtering, color-coding, Dynamic Querying and data sampling. It also provides summary information along with visualizations, and by maintaining a connection between visualizations and the source database, it Dynamically updates the summary information. To demonstrate how the presented visualization system provides capabilities for examining online store clickstreams, we present a series of parallel coordinates and starfield visualizations that display clickstream data from an operating online retail store. A framework for understanding Web merchandising is briefly explained. A set of metrics referred to as micro-conversion rates , which are defined for Web merchandising analysis in our previous work (Lee et al., Electronic Markets, 2000), is also explained and used for the visualizations of online store effectiveness.
Edith Schonberg - One of the best experts on this subject based on the ideXlab platform.
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Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising
Data Mining and Knowledge Discovery, 2001Co-Authors: Mark Podlaseck, Edith Schonberg, Robert HochAbstract:Clickstreams are visitors' paths through a Web site. Analysis of clickstreams shows how a Web site is navigated and used by its visitors. Clickstream data of online stores contains information useful for understanding the effectiveness of marketing and merchandising efforts, such as how customers find the store, what products they see, and what products they purchase. In this paper, we present an interactive visualization system that provides users with greater abilities to interpret and explore clickstream data of online stores. This system visualizes the effectiveness of Web merchandising from two different points of view by using two different visualization techniques: visualization of sessions by using parallel coordinates and visualization of product performance by using starfield graphs. Furthermore, this system provides facilities for zooming, filtering, color-coding, Dynamic Querying and data sampling. It also provides summary information along with visualizations, and by maintaining a connection between visualizations and the source database, it Dynamically updates the summary information. To demonstrate how the presented visualization system provides capabilities for examining online store clickstreams, we present a series of parallel coordinates and starfield visualizations that display clickstream data from an operating online retail store. A framework for understanding Web merchandising is briefly explained. A set of metrics referred to as micro-conversion rates , which are defined for Web merchandising analysis in our previous work (Lee et al., Electronic Markets, 2000), is also explained and used for the visualizations of online store effectiveness.
Alexandros Labrinidis - One of the best experts on this subject based on the ideXlab platform.
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hash based overlay partitioning in unstructured peer to peer systems
Parallel Processing Letters, 2009Co-Authors: Harris Papadakis, Paraskevi Fragopoulou, Evangelos P Markatos, Marios D Dikaiakos, Alexandros LabrinidisAbstract:Unstructured peer-to-peer (P2P) networks suffer from the increased volume of traffic produced by flooding. Methods such as random walks or Dynamic Querying managed to limit the traffic at the cost of reduced network coverage. In this paper, we propose a partitioning method of the unstructured overlay network into a relative small number of distinct subnetworks. The partitioning is driven by the categorization of keywords based on a uniform hash function. The method proposed in this paper is easy to implement and results in significant benefit for the blind flood method. Each search is restricted to a certain partition of the initial overlay network and as a result it is much more targeted. Last but not least, the search accuracy is not sacrificed to the least since all related content is searched. The benefit of the proposed method is demonstrated with extensive simulation results, which show that the overhead for the implementation and maintenance of this system is minimal compared to the resulted benefit in traffic reduction.
