We are in a new era of the Internet. Static web pages are yesterday’s media. Now, business is driven by social messaging, conversations, and constantly flowing data. We call this The Stream.
As The Stream has emerged, the driving force of online attention has shifted from search to discovery, and from the static Web to social media and all forms of streaming data. But social conversations have also become overwhelmingly noisy; it’s getting harder to find what matters in all the chatter.
How do you make sense of this real-time landscape?
How do you filter signal from noise in the Stream?
Search engines are not the solution. They index the past, not the present. They’re great for finding Web pages, but no match for the real-time social Stream. We need a new approach: Trend Intelligence from Bottlenose.
In the enterprise, today’s real-time emergency is in marketing, due to the explosion of social expression affecting brands. However, soon all enterprise functions will operate under similar real-time pressures imposed by The Stream. Our Trend Intelligence solutions will take in all forms of stream data, internal and external, for a master, cross-correlated view of actionable trends in all the real-time forces affecting your business.
Bottlenose builds a real-time cognitive map of every topic, much like the human brain. It then uses sophisticated techniques for selecting and surfacing “trends with shove” from time-series data. We call this Trendfluence, allowing you to identify, anticipate and instigate trends that drive your business.
Think of Bottlenose Nerve Center as a Now Engine™. It scans and illuminates the present and shows you a live view of activity. It makes sense of what’s happening now, and helps you discover what’s important and what’s changing, as it happens, not after the fact.
Blend in historical data from Streams to replay past events as though they are happening now, to better understand past phenomena. Or use historical analysis to put emerging trends in a context of established patterns that shape your business.
Bottlenose Nerve Center spots real-time trends, tracks interests, measures conversations, analyzes keywords and identifies influencers. As we expand our library of data sources and aggregate the content, people, thinking and emotion of humanity’s connected communications, Bottlenose will map, reflect and explore the evolving global mind. We aim to continuously show what humanity is thinking and feeling, now.
Bottlenose provides real-time trend detection and discovery using a new technology called StreamSense™ (27 pending patents). StreamSense™ combines specialized natural language processing, data mining, emotion analysis, statistical algorithms and machine learning heuristics.
StreamSense™ ingests real-time streams of unstructured data from social media, enterprise applications, Web applications, newswires, market data, email, and other sources. It continuously data-mines to detect an unlimited range of entities and relationships as they emerge and develop, including topics, phrases, opinions, links, people, organizations, events, and the connections between them.
StreamSense™ runs in the cloud where it continuously maintains a live semantic map of all detected entities and their interrelationships. This map functions like an “artificial brain” that can be used to detect , query, and visualize patterns and trends in real-time streams.
Applications of StreamSense™ include:
The StreamSense™ engine is composed of several different layers that run in the cloud. It leverages numerous big data storage and processing technologies like Cassandra, HBase, Impala, Redis, ElasticSearch and Storm.
The analysis process starts with Sponge - a customized natural language processing component that extracts entities from micro-content. Sponge identifies topics that were not previously known in any database (for example the name of Lady Gaga’s latest album). Also, it classifies messages based on a growing curated ontology of 140 semantic types (complaints, endorsements, moods, news, questions, answers, coupons, etc.).
Next, in Psychographic Analysis the data is further enriched by doing automated sentiment analysis, psych profiling and demographic classification. This gives us a wide variety of entities and data points to analyze.
In Trend Analytics the entities and data points are converted to time series data that can be used in reports and visualizations.
In the Trend Graph & Detection layer we build a graph of the entities and their relationships. We do this by extrapolating time series data around entities using statistical approaches (like FFT) combined with machine learning heuristics (like SVM) to get a continuous stream of detection events around entities. These events are then clustered to provide high-level overviews of new patterns. In the future we plan to expand this layer into a more fine-grained world model in which all observations and corresponding emotions are mapped — much like the human brain.
Finally, there is the Agents layer in which we combine user configurations and interests to provide a continuous stream of intelligence events around people, topics, companies, competitors and industries.
Serial Internet entrepreneur, expert on product development, search, social media and artificial intelligence. Co-founded EarthWeb in 1994 (IPO:1998), which also spun out Dice.com (IPO:2007). First investor in Klout.com. Co-founded SRI nVention Incubator and worked on the DARPA CALO project (the original technology behind SIRI on the iPhone). Founded Lucid Ventures and Twine.com (first consumer semantic search engine). Co-founded Live Matrix (Sold to OVGuide), The Daily Dot (the newspaper of the Internet), and StreamGlider (next-gen newsreader platform). Angel investor in Cambrian Genomics, Energy Magnification Corp. and Space Adventures. Advisor to Common Crawl Foundation, Publish This!, Sensentia. Worked at Thinking Machines and Kurzweil, Individual Inc. More than 50 patents. Flew to the edge of space in 1999.
Has built complex information systems since age sixteen. Incubated numerous web products (big data, social and semantic web). Created and ran development teams in Europe, Japan and US. Former CTO of Cerego Japan (iknow.jp). Owner at Synaptify.com (advisor to several startups in EU and Asia). Bachelor in Intelligent Systems Engineering.
34 year career working alongside founders to build & expand businesses in innovation markets. 27 years exclusively in B2B software & internet, in senior marketing and operating roles, including Lotus Development Corp (public), Callidus Software (IPO CALD 2003), inquiry.com (acquired 1997), Gupta Corp (public), Nantucket Corp (private, acquired 1992), Continuus (acquired 1999); CEO Big Stage Entertainment (acquired 2010), CEO Seymour Duncan; VP Clearstone Venture Partners (VC, 6 years, dozens of companies); Operating advisor to multiple venture-funded & bootstrapped companies. Drove demand for over $1B of new product sales.