Abstract
Information over the Web is rapidly becoming event-centric with the next age of WWW projected to be an EventWeb in which nodes are inter-connected through diverse types of links. These nodes represent events having informational and experiential information and analysis of these events has a substantial semantic impact regarding enhancement of information search, visualization and story link detection. Information regarding semantics of EventWeb connections is also important for event planning and web management tasks. In this paper, we devise and implement an event algebra for detection and analysis of event connections. As compared to traditional solutions, we process both context-match operators and analytical operators, cater for all event information attributes, and define the strength of connections. We implement a tool to evaluate our algebra over events occurring in the academic domain. We demonstrate an almost perfect precision and recall for context-match operators and high precision and recall for analytical operators.
Highlights
The web of documents or web of information is converging towards a web of events, which has been typically labeled as the EventWeb, in which each node represents an event which has both informational as well as experiential data, and which is connected to other nodes through different types of links, i.e., referential, structural, relational, and causal [1]
Extracting important information regarding connections between events appearing over EventWeb is an existing requirement of the Web community
We have developed an event algebra that extracts semantic information from EventWeb by identifying potential connections between events
Summary
The web of documents or web of information is converging towards a web of events, which has been typically labeled as the EventWeb, in which each node represents an event which has both informational as well as experiential data, and which is connected to other nodes through different types of links, i.e., referential, structural, relational, and causal [1]. The focus of this paper is to enhance state of the art research in extracting semantic information from EventWeb. Our research objective is to process the contextual event information to detect linkages between events, based on the following three objectives: 1) detecting stories that exist along events but are unseen, 2) enhancing information search and visualization experience over the web, and 3) constructing a formal and extensible representation for representing linkages between events. Our research objective is to process the contextual event information to detect linkages between events, based on the following three objectives: 1) detecting stories that exist along events but are unseen, 2) enhancing information search and visualization experience over the web, and 3) constructing a formal and extensible representation for representing linkages between events To this end, we devise and implement an event algebra for representing and analyzing different connections between events over EventWeb. We generate useful information regarding these connections. We obtained an almost perfect precision and recall of 99% and 97% with context match operators, and a high precision and recall of 89% and 78% for analytical operators
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