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Www.rosoka.com Connecting the Who and the What with the When and the Where April, 2015.

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Presentation on theme: "Www.rosoka.com Connecting the Who and the What with the When and the Where April, 2015."— Presentation transcript:

1 Connecting the Who and the What with the When and the Where April, 2015

2 Tokenization Entity & Relationship Extraction Language Identification Anaphora Resolution Salience Determination Entity-level Sentiment Analysis Geospatial Tagging & Resolution MEET ROSOKA Turn Big Data in to smart information with Rosoka. Start with unstructured documents in the most popular formats and Rosoka will glean and connect the important information.

3 SCALABLE PORTABLE MULTILINGUAL Rosoka works with any amount of data. Use Rosoka on Mac, Windows, or Linux. Rosoka understands over 230 languages. Bonjour こんにち は Hello

4 ENTITY EXTRACTION Based on the style and tone of language used in a document collection, key things are discovered, along with their importance and sentiment. PERSON Place OrgDates Phone Facility

5 RELATIONSHIPS Predicate Subject Object (PSO) statements connect the key things together. Rosoka PSO’s are very easy for triple stores and visualization tools to use. PERSON OrgPlaceFacilityAddressPhone URLIDNUMMoneyMeasureDate

6 IDENTITIES Rosoka recognizes the identity of things across document and language boundaries through its understanding of Language and linguistic context. BOKO HARAM Boko Haram боко харам 보코 + 하람 ボコ · ハラム 博科圣 地 בוקו חראם بوكو حرام

7 MODULAR Rosoka plays nice with others. With a Java API and REST web service interface, Rosoka makes it easy to handle formats like Word, PDF, and TXT with XML and JSON outputs. We even provide sample code to make it cut-and-paste simple.

8 Why design every time? Entities & Triple Store Full Text Indices Admin Collector(s) Data Access Scalable Cloud Framework When you can select options?

9 Create with off-the-shelf products Entities & Triple Store Full Text Indices Admin Enterprise scalable technologies. Works on a standard server or massively parallel within the Cloud.

10 Determine data needs What data sources do you need to solve your problem? Search Discover Compare/Contra st Network Find Report Annotate

11 Choose the analytical actions What questions do you need to answer to solve your problem? Search Discover Compare/Contra st Network Find Report Annotate

12 Present the information What user experience do you need to solve your problem?

13 $ REDUCE COSTS Flexible licensing No additional modules to buy Value in volume SAVE TIME Simple integration Easy to tune Fast ingest ! AVOID RISK Less moving parts Industry standard APIs Industry standard outputs

14 We like hard problems… Can we help you solve one?

15 Rosoka Software Inc. 950 Herndon Parkway Suite 280 Herndon, VA USA +1 (703)

16 Backup

17 Knowledge Acquisition Compositional Dynamic Rote Nicholas Cage Julia Roberts NicholasJulia Roberts Cage Chinua Achebe is a Nigerian author. ChinuaAchebe Chinua Achebe

18 Delivery Methods

19 Direct Licensing Individual Instance Licenses –Term or Perpetual license for small to modest number of instances. Site Licensing –Term license for an unlimited number of instances at a given facility or named Cloud. Enterprise Licensing –Term license for an unlimited number of instances within a given organization, regardless of geographical location. Cloud Licensing Amazon EC2 –Term license available as a web service from AWS as an AMI. Reseller Licensing VAR OEM –White Label –Black Label Development Licensing Educational –Term license that covers a pre- determined number of non- production instances for research institutions or universities. Integrator –Term license that covers an unlimited number of non-production instances for use in IRADs, demonstrations, and proof-of- concept projects. Product Licenses Offered

20 Feature Integrated Language ID Text conversion of DOC, DOCX, PDF, XML, and HTML Native entity and relationship extraction in over 230 languages Integrated SALIENCE that provides importance of entity to its document Integrated POLARITY that provides sentiment of entity to its document Extensible extraction and relationship ability Document viewer GUI to see extraction results for extraction and relationship refinement Machine learning for new entity components Integrated geotagging ability for PLACE, FACILITY, and GEOCOORDINATE entity types


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