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Semantic Verses: Klangoo

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Presentation on theme: "Semantic Verses: Klangoo"— Presentation transcript:

1 Semantic Verses: Klangoo
Dr. Brand Niemann Director and Senior Data Scientist Semantic Community February 24, 2014

2 Web Page

3 Topics Solutions: Demos: Audience Engagement:
Text analysis technology that provides an automated solution for content generators Search Engine Optimization: Choose the best meta-tags (semantically) allowing higher visibility to search engines Media Monitoring: Magnet monitors your news and media coverage Demos: Bloggers: How does magnet enrich your content? Search: See how magnet sets the best search standards In the Lab: Check out the tools we are building

4 Banners Real time text summarization Topically relevant content
Real quantifiable results magnet Audience engagement solution Automated customized pages magnet text analysis understands what the text is about

5 Options Audience Engagement Solution: Showcase Developer Community
How did magnet affect the "The Daily Star" user engagement experience? Increased Page Views Increased Time Spent on Site Decreased Bounce Rate Increased Registered Users Learn more about the audience engagement solution. Developer Community Use magnet's unique semantic capabilities to: Create your own cool tools Power your website, product or business Click here to get your free API license key, sample code and related documentation.

6 Showcase

7 Audience Engagement Solution

8 The Daily Star

9 Register

10 Options Try Our Free Service: Try Our Demo Live:
This demo allows you to search the latest 1 MM articles collected from several news sources online that our magnet service crawls on a daily basis. Try Our Demo Live: This demo allows you to add Meta Data/Description to any entered text. This ensures your page gets the best search traffic possible.

11 Searching Searching: last several days of news articles. More info.
This is NOT a keyword system, therefore, for optimal results, you must enter enough text to make-up a clear subject matter. Enter or paste an active article, a couple of paragraphs or a few well-written sentences about some story that appeared recently in the news.

12 More Information Our Semantic Search finds related articles to the text you entered from a database containing the latest articles fetched from the top online news sources. What languages does this Search support? We currently retrieve articles from English and French sources, translate them using Bing Translator, and process accordingly. Other languages will be added successively starting with Spanish, then German, Hebrew, Chinese (Simplified), Arabic, Russian, Swedish, etc. Users can provide their subject matter in any language and will always receive multilingual results. Concerning retrieved articles, what retrieval accuracy should I expect? The Semantic Search results are all automatically generated using our proprietary semantic technology, and, therefore, rely totally on the topical similarity between the entered subject of interest and the processed news articles. Hence, the retrieval accuracy is strictly related to the quality of search query.

13 News Sources ABCNews AFP AlJazeeraEnglish AssociatedPress Bloomberg CHOW CNETTV CNN CNNInternational Content Marketing Institute The Daily Star Lebanon Data Driven Journalism Diginfonews eMarketer IJNET Ipsos itnnews KMWorld Knowledge Wharton Mashable MilitaryChannel NDTV Nieman Journalism Lab NMATV, NMAWorldEdition PBS ReutersVideo RussiaToday skynews TEDtalksDirector telegraphtv ten The Next Web the Onion TheNewYorkTimes TheYoungTurks TopRank Wambda whitehouse WorldEconomicForum

14 News

15 Videos Please note that our videos database is currently still very small, although it is continuously being updated.

16 Images

17 Semantic Verses Magnet
“Magnet is the only engine that treats topics as semantic objects, which gives it a competitive edge since the identification of “key topics” is generally considered to be the main feature of any semantic engine.” “Semantic is used here to refer to understanding what a piece of text is about. We do not claim we are doing NLP/NLU for question/answering purposes.” Source: Walid S. Saba, PhD, AI/NLP Scientist, February 2014.

18 MindTouch MindTouch: Semantic Community:
Treats topics as semantic objects (they can be searched for links to content). MindTouch headings identify “key topics” (see Table of Content for book in this page). Allows one to construct a natural language front-end for enterprise data (and big data) integration across multiple sources (Google Chrome and Spotfire can Find words and data in their mashup Knowledge Bases). Can be combine with Be Informed, YARCData, and big data analytics (Spotfire) and could pilot including Semantic Verses. An example of expert subject matter that serves to provide a metamodel of topics as an interface to the integration of content (text and data) that can be both personalized by the user and integrated with similar metamodels. Semantic Community: Doing Natural Language Processing (NLP)/Natural Language Understanding (NLU) by hand in MindTouch and I see why it is so difficult to automate for massive information on the Internet without Subject Matter Expertise and Structure.

19 Semantic Verses Do a pilot where one can see immediate results of the use of our semantic technology on the Washington Post website. The Washington Post is one of MindTouch’s clients. Open up the possibility of semantically enabling the help desk/customer support technology of MindTouch. Try:

20 Suggestion: Apply to Scientific Nanopublications

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