Bridging CONTENT and object with HOLTRAN Technology

1. Bridging CONTENT and object with HOLTRAN Technology “The challenge… isto find effectivesolutionsto unlock the valuefrom unstructured information sources, and to leverage it in Business Intelligence deployments” Butler Group “Poor classification costsa 10,000 user organization $10M annually.” Usability expert Jacob Nielsen “unstructured information doubles in quantity every three months” Gartner Group “in modern enterprise, 85% of data is unstructured” Butler Group

2. HOLTRAN(Higher Order Logic Translation) Technology fills the gap between unstructured texts and structured data. The social impact of HOLTRAN in the next 10 years will cover the following situations: • Two or more people talking over the "phone" each in his native language and receiving the answer in it. • Traveling in a car one can ask "it" any question and receive the system response in his native language. • One can receive ANY "newspaper" in his native language (the first step to be done through our participation in DigiNews !). • Fully automated call centers: each user can be receive the answer in his native language. • Translation form one artificial language to another providing full database compatibility without additional software development (solution of PDM-ERP compatibility problem). • No manual transaction treatment: all e-mails read and treated automatically (Spam as well).

3. For DigiNews project we shall supply HOLTRAN Engine together with a set of standard HOLTRAN applications for • text analysis (Content Management (CM), Personalisation) • categorisation • clustering • summarisation (CM) • metadata extraction • merging • question answering.(CM and Return Channel)

4. HOLTRAN Categorisation and Clustering application. (Content Management and input for Personalisation) Functionality: • automatic categorization of textual documents by pre-defined categories • clustering a set of textual documents by automatically extracted categories • Automatic building of hierarchical contextual taxonomies Features: • provides highest possible accuracy (not worse than by a human expert, taken as 100%) of categorization by pre-defined categories (the State-of-the-Art accuracy of text categorization systems yet varies between 60 and 90%) • categorizes and clusters documents basing on their semantic content • builds new categories either automatically or by user-provided rules • supports multi-lingual and hetero-lingual document sets • supports extensible and adjustable category definitions • supports hierarchically organized categories (taxonomies) • supports multiple document versions

5. HOLTRAN Information Search ("Question answering") application (Content Management and Return Channel ) Functionality: • semantic-content-based search of information in a set of textual documents • comparison of documents contents for detecting redundancies and contradictions • merging related information from multiple textual documents Features: • accepts user requests (questions) in the free textual form (natural language) • represents responses in a natural language as well • performs search of requested information basing on documents semantic contents • extracts precise and specific answers to user's questions (optional referencing to source documents) • though is able to detect, but remains tolerant to contradictions and redundancies between different sources as well as between different parts of a single source • when answering a single question generally might summarize (merge) information extracted from multiple sources • may ask the user for a clarification if a request is formulated in the terms unknown to the system or in cases of redundancies, contradictions or vagueness in the question • is able to automatically extend its dictionaries when encountering new terms in a known context • supports multi-lingual document sets and multiple user communication languages

6. Main challenges & identified co-operation • Creation of fully automated publishing platform sufficient to provide the several times a day issue of a digital newspaper with constant updates and fully automated return channel HOLTRAN Engine based Content Management System will form the basis for Data Search and Analysis of Incoming News Flow, Newspaper Contents and its representation in publisher platform and user terminal. Identified partners: • Philips PDSL (General Architecture) • Concentra (Publisher’s Platform, CM) • dZine(Content Management) • Ibermatica (User Profiling) • KTH (Content filtering) • Six Offene Systeme ( Content Management, User Profiling) • Other partners are also welcome.

7. HOLTRAN Technology can potentially serve as a universal international standard of representation, storing and exchange of information aimed to integrate all the currently existing information technologies and to promote them to a new level of intelligence.