GlobalWisdom Software Bravo TM Reviewer for Online Editors Abhijit Patil

Company Overview GlobalWisdom, Inc. sells software that dramatically increases the ROI (Return Of Investment) of enterprise information management systems by capturing, organizing and sharing individual and collective knowledge. Software enhances content and knowledge management systems by leveraging existing workflows and continuously adapting information structure to foster critical thinking Software is not smart; people are Software that captures the distributed expertise of people working with content.

Bravo TM Reviewer for Online Editors Workflow-based solution for the online publishing market. Effectively leverages the expertise of editors in charge of adding metadata to content. Online publishers depend on high quality metadata to make sure their readers find the information they need. Bravo makes the process of adding metadata more efficient and effective, so publishers can maximize their return on investment when producing value added content.

The Value of Bravo™, Software that Learns Producing high-quality metadata is expensive. The best metadata comes from –Editorial oversight by employees who understand the content –The taxonomy (i.e. subject matter hierarchy) being applied to the content –The customers whose business needs are being served. Auto-classification –Reduces cost –Without human oversight and control, create metadata that makes more sense to an algorithm than a human being.

The Value of Bravo™, Software that Learns (Cont.) The Bravo combines –The efficiency of auto-classification –The expertise of in-house editorial staff Allowing editors to train the auto-classification software within their ordinary workflow. This improves the performance of the auto-classification algorithms, so that business can achieve a more cost-effective balance.

Bravo TM System

How ? Auto-classifier recommends topics as metadata tags, which reviewers can quickly approve or change. This allows publishers to off-load the rote work to the software Gives reviewers tools to fine-tune the taxonomy while reviewing content. Can add negative or positive examples to the training set with a click of the mouse Easily create new topics or subtopics. These tools allow to produce better quality metadata

Bravo TM Modules The Bravo Module Concept Based Search –The difference between search and retrieval Content Classifier Content Indexer K42 Topic Map Engine

The Bravo Module (Features) Profiling Based on user/system interaction & direct input –Gathers feedback from how people already work with information Identification of subject area experts Recommendation of relevant topics or documents –Global Wisdom's search module is concept based - results are returned by the ideas expressed in a document, not simply by keywords Information alerts on preset topics, or relevant to the work at hand Automatic, accurate content routing

The Bravo Module (Features) Search Search by selecting example, from a sentence to a full document Merging two or more examples Free text System Unlimited hierarchy depth Augments performance of existing content management systems Integrates seamlessly with legacy data storage systems

Concept-based Search Module™ Search Module is concept-based, not keyword- based. Can find highly relevant documents in which query terms do not appear. Users can phrase queries in the ways that make sense to them, rather than adapting to the limitations of the search engine. Based on patented Latent Semantic Indexing (LSI), which has demonstrated a 30% increase in accuracy (Telcordia, 1999) over keyword techniques. Leverages user feedback to become fully adaptive.

Concept-based Search Module™ (Cont.) Sample Applications Corporate intranet - ensure that employees across the organization can find the information they need. Maximize reuse of information, minimize duplication of effort. Workgroup collaboration - improve support for research, analysis, project management, and more. Publishers - ensure that customers can locate the valuable content they need. Corporate extranet - improve accessibility to timely, accurate information for suppliers, end users and partners

Concept-based Search Module™ (Cont.) Features : Search by example. –Select a piece of text, from a sentence to an entire document, to serve as a search query. Search by merging examples. –Combine two examples to find documents that are relevant to each. 100% automatic. –Does not require thesaurus or controlled vocabulary (works with multiple languages, without the need for translation). Concept-based relevancy ranking. Highly effective with Optical Character Recognition (OCR). Retains high level of accuracy with small amount of text, e.g., photo captions.

Latent Semantic Indexing Uses singular-value decomposition. We take a large matrix of term-document association data and construct a "semantic" space wherein terms and documents that are closely associated are placed near one another. Singular-value decomposition allows the arrangement of the space to reflect the major associative patterns in the data, and ignore the smaller, less important influences. As a result, terms that did not actually appear in a document may still end up close to the document, if that is consistent with the major patterns of association in the data. Position in the space then serves as the new kind of semantic indexing, and retrieval proceeds by using the terms in a query to identify a point in the space, and documents in its neighborhood are returned to the user.

D-GPS™ Content Classification Module Classifier uses a model-based approach Current algorithms simply analyze the text in a document. But different people will interpret the meaning of that information in their own way. Patent-pending algorithm, D-GPS, improves accuracy and relevance by simultaneously analyzing the text and the hierarchy, or hierarchies, that reflect the understanding your business brings to information. Scalability – Handles large document sets with ease Integrated with existing hierarchy or with custom one

GlobalWisdom Indexer Essential component of the bravo™ engine, which leverages user feedback to deliver fully adaptive enterprise workflow solutions for publishers, content delivery, knowledge management and enterprise portals. Features : –Fast, reliable and accurate indexing of content using Java and SQL DBMS. –100% Java. –Parallel threads using multiple DBMS connections. –All common formats, including text, HTML, XML, etc. New formats available on request. –Optional Crawler API, with support for focused crawl

K42 Topic Map Engine Using the Topic Map standard, K42 captures the relationships and associations that connect your data in within a "knowledge layer.“ Allows a greater level of meaning to be represented within a content or knowledge management system, improving the performance of critical information applications. –For example, Topic Maps can represent that pending FDA regulations have influenced a biotech company to launch a new marketing campaign, and that both have contributed to a rise in stock prices. The knowledge layer is a neutral format that works on top of any proprietary system, easily bridging multiple formats and sources. When integrated with the bravo™ engine, K42 leverages user feedback to become fully adaptive.

References Project Home Page – – Indexing by Latent Semantic Analysis – –