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Semantic webslideshareversion
1. Breakthrough Content Discovery
and Text Analytics Technology
by Eric Forst – CMO Synapsify
at the LA Semantic Web MeetUp
Cross Campus
Santa Monica, California
August 6, 2013
2. Vital Statistics
Headquarters
Washington, DCSatellite
Los Angeles
$750k
Raised seed round
with ICG Ventures as
lead investor
3 IP
1 patent granted
2 patents pending
4 Clients
2 Market Research (beta)
1 Social Media
1 Product Review (beta)
Cloud-based
Product Ready
3. The “Synapsifier”
• The origins of humanity have become lost
and enshrouded in myths and theories.
• Finding himself amongst people whose
language and culture he cannot hope to
understand, the book’s hero, Schwartz, is
made a test subject for a machine called
the Synapsifier.
• The machine increases human learning
capacity by increasing synaptic
discharges, but it also has an annoying
habit of killing most of the animals it has
been tested on to date.
14. Phonemic Based Text Analytics
pho·neme
noun fō-nēm
: any of the abstract units of the phonetic system
of a language that correspond to a set of similar
speech sounds (as the velar k of cool and the
palatal k of keel) which are perceived to be a
single distinctive sound in the language
16. “One way of looking at language overall, is to
say that life would be meaningless without
stories…and that language would be
meaningless without stories about intent.”
– Lawrence Au
26. Emotional Intelligence for Better Analytics…
Adaptive, intelligent software
that learns from every piece of
text analyzed.
Based on natural patterns of
sound and meaning mapped by the
brain in the formation of narrative.
Technology that empowers
other technology.
An API-based business model that
powers direct enterprise
relationships, start-ups and developer-
communities.
Apps will include text-
editors, recommendation engines, content
management systems and
intelligent robots.
Our patented technology performs contextual analysis of sentiment in text directly from phonemic data. We bypass dictionary-based emotion analysis for greater accuracy, which also eliminates dictionary construction labor costs. Synapsify performs automatic analysis of writing quality for story development and resolution of story tension. This allows for more accurate word sense disambiguation based on resonance of metaphors and emotions. We offer support for search queries composed of any length by suppressing irrelevant semantic links, which improves speed and accuracy and allows a query to be an entire book, article or post . For content libraries, this means you can offer thematically-based search engine results and intelligent recommendation engines. For online publishers, it means you can cluster the best-written and most thematically similar user-generated comments for a higher-quality reading experience. Our latest release supports the automatic creation of dictionary entries by analyzing text, an analysis of causality implied by text in all written content and social media. Our next release will support an analysis of implied intentions in text, such as purchaser intent and purchasing funnels, and it will allow for automated editorial guidance generated from automatic search comparing historic causal outcomes of possible alternative conversational intentions.
