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Automatic Hyperlinking | | | Clustering | | | Query Guidance |
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Automatic Clustering
IDOL's automatic clustering enables unprecedented visibility of the information and knowledge stored in the enterprise by creating a real-time map, organizing the unstructured content exchanged in emails, telephone conversations and IM.
Automatic clustering allows organizations to analyze large sets of documents and even user profiles and automatically identify inherent themes or information clusters. A filing cabinet disaster serves as a useful metaphor here. Imagine a cabinet stuffed with information on different topics. If the cabinet fell over and all of the documents scattered on the floor, it would take days for a human being to go through manually and refile everything accurately. IDOL is capable of reading through all of this information in real-time, identifying "clusters" of related information and automatically sorting it into appropriate piles for easy and immediate access. In essence, automatic clustering creates order out of chaos. There are many ways that IDOL's clustering capability can be used. For example, the "what's hot" feature can automatically detect burning topics in an organization's information assets. An enterprise can literally watch itself think as clustering identifies areas and ideas that attract the most attention as well as areas that do not. In addition, IDOL automatically identifies and displays the latest available information or "breaking news," alerting users in real-time to new areas of information or individual interest.
Key Benefits
Quantum Clustering
Autonomy technology continues to innovate by applying advanced mathematics to solve technical challenges. Using quantum mathematics to calculate states/concepts within data, conceptual information is more easily and accurately identified. Quantum wave functions are generated around the data, leading to global, stable results without relying on sampling. Quantum clustering also proves to be highly scalable, as the ability to cluster incrementally (instead of recalculating the entire set upon change in data) reduces the amount of information processing required.
Cluster Visualization
IDOL provides four intuitive Java-based user interfaces for cluster visualization:
Spectrograph Pane
This user interface displays the relationship between clusters in successive periods and sets of data. Clusters are presented as a JSP- based spectrograph: the x-axis represents information over time, enabling users to visualize how clusters develop over a given time period; the y-axis represents the range of concepts defined within the knowledge base.
The spectrograph can display hot and breaking news in the same instance. By scrolling over the spectrograph, titles are automatically generated and assigned to every cluster. By clicking on the cluster, the results can be viewed. The importance of clusters over time can be seen through the change of color and width. The color and intensity of the lines are indications of the size of a cluster. The brighter colors indicate "what's hot" while the width of the lines is an indication of the volume of information on that topic.
2D Cluster Map
The 2D cluster map is an alternative visualization tool to the spectrograph, used to identify conceptual similarities and differences between clusters. Also based on JSP, the landscape is generated from the inter-relationships between clusters and the documents contained within those clusters. Designed to provide a single overview of the clusters contained within the data, clusters that are close together correlate to higher degrees of similarity, while dissimilar clusters are situated further apart. Navigation features are identical to the spectrograph pane, enabling users to browse clusters with a click of the mouse.
3D Cluster Map
The 3D cluster map, which operates in the same way as the 2D cluster map, offers users yet another option for visualization.
Geo-Cluster Map
IDOL has enhanced its support for geo-efficiency by providing visualization tools to represent document density per location, thus allowing the administrator to quickly assess usage patterns and make informed decisions about load balancing. IDOL's flexible distribution design already allows data to be stored in the most sensible location based on bandwidth, lag time and availability/demand; this added feature aids in achieving maximum performance for a large and globally dispersed number of users and volume of information.
| Functionality |
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Automatic Hyperlinking | | | Clustering | | | Query Guidance |
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