Expert System. Deep Semantic vs. Keyword and Shallow Linguistic: A New Approach for Supporting Exploitation

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1 Expert System Deep Semantic vs. Keyword and Shallow Linguistic: A New Approach for Supporting Exploitation Rita Joseph Federal Government Operations Expert System

2 Who we are Expert System is the largest, fastest growing semantic software company in the world. We develop technology, applications and solutions to extract, understand and share information more effectively. 2

3 Established market presence Expert System was established in Modena, Italy by three young programmers with an idea. A few months later, Expert System s software was integrated into the Microsoft Office suite. Private and Profitable with Revenue doubled in the last three years to over $15 million in 2010 and EBITDA above 20%. 30% of resources devoted to R&D and over $14 million invested in the last 3 years, with $5M more planned for the next 2 years. More than 100 employees and offices in Italy, London, Washington, D.C. and Chicago. 3

4 Recognized for mature and proven technology Identified among the world s leading information access technology developers. Selected one of the Innovative Information Access Companies Under $100M to Watch. Recognized for text analytics and superior SharePoint integration capabilities. One of the few non-microsoft technologies in the MS Office suite. 4

5 A flood of unstructured data & information More than 80% of the knowledge on which our daily jobs are based is unstructured ( s, documents, web pages, articles, information from social media, etc.). Over 294 Billion s sent daily. Over 6.1 Trillion text messages sent in And what about phone calls, faxes, chat sessions, etc.? Sources: Radicati Group, ITU.

6 The limits of traditional approaches Keyword Technology or Statistics Shallow Linguistic Technology Breaks text into single words without considering the context, like reading a language that we don t understand: Recognizes words and identifies their most basic forms (lemmas), but cannot distinguish between different meanings. Az IBM szokásosan nagy hangsúlyt helyez a továbbképzésre, így munkatársai évente számos szakmai tanfolyamon vesznek részt. Sell -> Selling -> Sold Neither understands the meaning of words. 6

7 Where semantic technology excels One keyword, many different meanings. Over 231 million results for a single query. 7

8 The information we need is harder to find The increasing amount of information 15 Petabytes of new information a day 15 million searches a month Productivity of search The diminishing effectiveness of search 1/3 of searches do not find intended results Over two hours a day are spent searching for information Desktop PC Era Directories Files & Folders Web Social Web Keyword Search (Google) Tagging Semantic Web Natural Language Search Databases Amount of information 8

9 Why we are different Semantic technology understands the meaning of words in the same way you learned to read. It understands the relationships between words. Luke (subject) has eaten (verb) a chicken (object). It understands the meaning of words. To eat (chicken); to consume (oil); to destroy (sweater); to spend (money); to rust (the tower), etc. 9

10 Next generation technology

11 The problem of text analysis Same word, different meanings Jaguar (animal) Jaguar (car) Different words, but the same meanings Disability Legislation Equal Opportunity Law Different words, related meanings Organization à Company Organization à Charity Organization à Trade Union 11

12 How Cogito works 12

13 What is a semantic network? A rich map of associations and meanings of words. Includes all definitions of all words. Includes relationships between all words. The quality of results is derived from the richness and complexity of the semantic network. COGITO English Semantic Network: 350,000 words 2.8M relationships 13

14 The semantic net, the heart of Cogito Traditional technologies can only guess the meaning of words using keywords, shallow linguistics and statistics. Instead, semantic networks can identify: Terms Abbrev. Concepts San Jose is an American city. Phrases Connections Domains Meanings San Jose is a geographic part of California. 14

15 Technology stack 1. Morphology 2. Grammatical 3. Logic 4. Disambiguation Development Studio 90% Precision Linguistic Query Engine 80% Precision English Semantic Network Arabic Italian Semantic Network Semantic Network German Other Middle Eastern Develop and Add Custom Rules Superior technology, tools and customization services maximize the quality and the performance of the solution. 15

16 The objectives of IT All areas where semantic technology plays a critical role. Source: AMR Research 16

17 How Expert System is unique The Cogito semantic platform improves the quality of results, and excels in: Productivity of search Recall. Retrieves more relevant information through search. Precision. Retrieves a high level of accurate results that are relevant to your query. Speed. Finds information quickly. Amount of Information 17

18 Contact us Thank You! Rita Joseph 18

19 Expert System in the news 19