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Celebros Launches Natural Language Processing Ecommerce Extension with Seven Conversions

March 9, 2016

An e-commerce site search company, Celebros, shared a news release touting their new product. Celebros, First to Launch Natural Language Site Search Extension for Magento 2.0 announces their Semantic Site Search extension for Magento 2.0. Magento 2.0 boasts the largest marketplace of e-commerce extensions in the world. This product, along with other Magento extensions, are designed to help online merchants expand their marketing and e-commerce capabilities. Celebros CMO and President of Global Sales Jeffrey Tower states,

“Celebros is proud to add the new Magento 2 extension to our existing and very successful Magento 1 extension. Celebros will offer the new extension free of charge to our entire Magento client base to ensure an easy, fast and pain-free upgrade while providing free integrations to new Celebros clients world-wide. The new extension encompasses our Natural Language Site Search in seven languages along with eight additional features that include our advanced auto-complete, guided navigation, dynamic landing pages and merchandising engine, product recommendations and more.”

For online retailers, extension products like Celebros may make or break the platforms like Magento 2.0, as these products are what add value and drive e-commerce technologies forward. It is intriguing that the Celebros natural language processing technology offers conversions available in seven languages. We live in an increasingly globalized world.


Megan Feil, March 9, 2016

Sponsored by, publisher of the CyberOSINT monograph

Italian Firm Adds to the Buzzword Blizzard in an Expert Way

March 7, 2016

I don’t pay too much attention to lists of functions an information intelligence system must have. The needs are many because federation, normalization of disparate data, and real time content processing are not ready for prime time. Don’t believe me? Ask the US Army which is struggling with the challenges of DCGS-A, Palantir, and other vendors’ next generation systems in actual use in a battle zone. (See this presentation for one example.)

I read “No Time to Waste! 5 Essential Features for Your Information Intelligence Solution.” I like the idea of a company (Expert System) which was founded a quarter century ago, urging speedy action.

You can work through the well worn checklist of entity extraction, links and relationships, classification, and sticking info in a “knowledge base.” I want to focus on one point which introduces a nifty bit of jargon which I had not seen in use since I was in college decades ago.

The word is anaphora.

There you go. An anaphora, as I recall, is repetition or word substitution. Not clear? Here are a couple of examples:


For want of revenue the investors were lost.

For want of a product credibility was lost.

For want of an application the market was lost.


The marketing cacophony increased and that drove off the potential customers.

Now you can work these points into your presentation when the users want actionable information which fuses available information into a meaningful output.

Because modern systems are essentially works in progress, buzzwords like anaphora take the place of dealing with real world information problems.

But marketing by thought leaders is so much more fun. That may trouble some. Parse that, gentle reader. What can one make in the midst of a blizzard of buzzwords? One hopes revenue which keeps the stock out of penny territory.

Expert System SpA, if Google Finance is accurate, about $2 a share. Roger, anaphora that.

Stephen E Arnold, March 7, 2016

Mondeca Demos

February 26, 2016

Curious about semantic technology. You may want to navigate to the Web site, read about the firm’s technology and professional services, and then explore its online demos. The page with various demos includes SPARQL Endpoint Status, a Temporal Search Engine, Linked Open Vocabularies, and eight other semantic functions. You can find the demos at this link. The Mondeca Web site is at

Stephen E Arnold, February 26, 2016

Startup Semantic Machines Scores Funding

February 26, 2016

A semantic startup looks poised for success with experienced  executives and a hefty investment, we learn from “Artificial Intelligence Startup Semantic Machines Raises $12.3 Million” at VentureBeat. Backed by investors from Bain Capital Ventures and General Catalyst Partners, the enterprise focuses on deep learning and improved speech recognition. The write-up reveals:

“Last year, Semantic Machines named Larry Gillick as its chief technology officer. Gillick was previously chief speech scientist for Siri at Apple. Now Semantic Machines is looking to go further than Siri and other personal digital assistants currently on the market. ‘Semantic Machines is developing technology that goes beyond understanding commands, to understanding conversations,’ the startup says on its website. ‘Our Conversational AI represents a powerful new paradigm, enabling computers to communicate, collaborate, understand our goals, and accomplish tasks.’ The startup is building tools that third-party developers will be able to use.”

Launched in 2014, Semantic Machines is based in Newton, Massachusetts, with offices in Berkeley and Boston. The startup is also seeking to hire a few researchers and engineers, in case anyone is interested.


Cynthia Murrell, February 26, 2016

Sponsored by, publisher of the CyberOSINT monograph

DirectEDGAR plus DtSearch Equals Superior Search for Analysts and Researchers

February 17, 2016

The article on PRNewswire titled directEDGAR SEC Edgar Database Research Platform Now Embeds The dtSearch® Engine for Enhanced Search and Retrieval discusses the partnership between dtSearch, AcademicEDGAR+, and AppsPlus. The merger is meant to improve advanced search for analysts and academic researchers who rely on search to enable them to wade through tens of millions of documents. Why did Dr. Kealey, CEO of AcademicEDGAR+ choose dtsearch? He explains in the article,

“We have over two terabytes of SEC filings and there was no other vendor whose offering allowed immediate access to any document in the results set no matter how many documents are returned.”  Dr. Kealey also notes that search granularity is critically important, and dtSearch’s unique operators extend far beyond the standard Boolean operators…To complete the implementation, AcademicEDGAR+ chose AppsPlus.”

AppsPlus has been around for over 15 years aiding in a huge range of development projects across industries. The article explains that with directEDGAR, users get more than just search. The product allows for extraction and normalization in one stop. That capability, paired with dtSearch’s instant search of terabytes, makes this partnership very exciting. Those academic researchers must be drooling into their elbow patches to get their hands on the new service.


Chelsea Kerwin, February 17, 2016

Sponsored by, publisher of the CyberOSINT monograph


Barry Zane and SPARQL City Acquired by Cambridge Semantics for Graph Technology

February 12, 2016

The article titled Cambridge Semantics Acquires SPARQL City’s IP, Expanding Offering of Graph-Cased Analytics at Big Data Scale on Business Wire discusses the benefits of merging Cambridge’s Semantics’ Anzo Smart Data Platform with SPARQL City’s graph analysis capacities. The article specifically mentions the pharmaceutical industry, financial services, and homeland security as major business areas that this partnership will directly engage due to the enhanced data analysis and graph technologies now possible.

“We believe this IP acquisition is a game-changer for big data analytics and smart data discovery,” said Chuck Pieper, CEO of Cambridge Semantics. “When coupled with our Anzo Smart Data Platform, no one else in the market can provide a similar end-to-end, semantic- and graph-based solution providing for data integration, data management and advanced analytics at the scale, context and speed that meets the needs of enterprises. The SPARQL City in-memory graph query engine allows users to conduct exploratory analytics at big data scale interactively.”

Barry Zane, a leader in database analytics with 40 years experience and CEO and founder of SPARQL City, will become the VP of Engineering at Cambridge Semantics. He mentions in the article that this acquisition has been a long time coming, with the two companies working together over the last two years.


Chelsea Kerwin, February 12, 2016

Sponsored by, publisher of the CyberOSINT monograph

Semantic Search: Yep, Everything You Need to Know about Semantic Search. Everything!

February 10, 2016

I love universals like “All men are mortal.” The problem is that there are not too many which click with me. I noted the write up “Everything You Need to Know about Semantic Search and What It Means for Your Website.” Very personal headline. I thought of my grandmother saying, “You should eat your spinach.” Yeah, right.

This write up is a search engine optimization take on “everything” about semantic search. Sure, there are some omissions, no code snippets, no examples of how to overcome computational bottlenecks, etc. But, hey, why quibble. This is 2016 and everything does not mean the “All men are mortal” reasoning. We are after clicks. We want sales leads. We want to be a maven.

The write up defines, illustrates with Google queries (getting smarter everyday, just maybe not with relevant results), dives into “ontology” with a diagram, gives a revisionistic glimpse of the history of semantic search, dips into the categorical affirmative barrel in “What Are All The Factors That Search Engines Use To Perform The Search?”, and offers an explanation of why semantic search is just better than old fashioned precision and recall. Oh, yeah. There is even a section which includes a superlative and this injunction:

Create high quality content.

Yep, eat your kale. Now.

If you want to become really good at semantic search, you may find that other information will be required. But, hey, this is 2016. Good enough is excellence. Close enough for SEO horse shoes is the name of the game.

Stephen E Arnold, February 10, 2016

How Often Do You Use Vocal Search

February 8, 2016

Vocal search is an idea from the future: you give a computer a query and it returns relevant information.   However, vocal search has become an actual “thing” with mobile assistants like Siri, Cortana, and build in NLP engines on newer technology.  I enjoy using vocal search because it saves me from having to type my query on a tiny keyboard, but when I’m in a public place I don’t use it for privacy reasons.  Search Engine Watch asks the question, “What Do You Need To Know About Voice Search?” and provides answers for me more questions about vocal search.

Northstar Research conducted a study that discovered 55% percent of US teens used vocal search, while only 41% of US adults do.  An even funnier fact is that 56% of US adults only use the search function, because it makes them feel tech-savvy.

Vocal Search is extremely popular in Asia due to the different alphabets.  Asian languages are harder to type on a smaller keyboard.  It is also a pain on Roman alphabet keyboards!

Tech companies are currently working on new innovations with vocal search.  The article highlights how Google is trying to understand the semantic context behind queries for intent and accuracy.

“Superlatives, ordered items, points in time and complex combinations can now be understood to serve you more relevant answers to your questions…These ‘direct answers’ provided by Google will theoretically better match the more natural way that people ask questions in speech rather then when typing something into a search bar, where keywords can still dominate our search behaviour.”

It translates to a quicker way to access information and answer common questions without having to type on a keyboard.  Now it would be a lot easier if you did not have to press a button to activate the vocal search.

Whitney Grace, February 8, 2016
Sponsored by, publisher of the CyberOSINT monograph

Semantic Mitosis: Attensity Splits Apart

February 7, 2016

Attensity is now two outfits. According to “Attensity Europe Breaks from US Parent Company.” The write up does not address the loss of synergy between the US and European sides of the semantic coin.

I learned:

The parties involved have agreed to not disclose any information on the purchase price or further terms of the transaction.

Not too helpful.

The news release points out that the European version of Attensity which is named Attensity Europe GmbH will focus on the customer support line of business; specifically:

the [Attensity Europe] company will focus on the growth segment of omni-channel customer service. Attensity Europe’s core product is the market-leading solution “Respond”, a multilingual and omni-channel response management software, which was designed by the German team of developers in Saarbrücken and has been systematically developed into the market-leading enterprise solution for omni-channel customer service over recent years.I assume that the US Attensity does not have a market leading product; otherwise, why not mention it? Omni-channel gets quite a bit of play. But I am not sure what “omni channel means.”

As an aside, Saarbrücken divorced itself from Germany: Once in 1925 and again in 1947. Might the water in the Saar be a factor in the split ups?

Many questions percolate through my discount coffee pot brain, but these are the questions I routinely ask when reverse mergers, no investment acquisitions, and de-synergies are at work.

My hunch is that US Attensity may have been perceived as slowing down the speeding bullet of Attensity Europe. Worth monitoring the situation.

Stephen E Arnold, February 7, 2016

A How to Create Jargon Tutorial

January 21, 2016

I read “Controversial Concepts: How to Tackle Defining and Naming Them.” The write up explains how to whip up jargon and get it into circulation. I thought, “Just what I need. I want to make ideas more confusing and more difficult to discuss. Hooray.”

Here’s the method:

  1. Name controversial concepts with proxy names such as “Greg”, “Mike” or “John” (or whatever name you prefer) to get potentially misleading names and their implicit connotations out of the way of progress.
  2. Draw a concept diagram showing those concepts as well as important semantic relationships among them.
  3. Formulate intensional definitions for each concept – still using the proxy names. Ensure that those definitions are consistent with the relationships shown on the concept diagram.
  4. Identify one or more communities that “baptize” those concepts by giving them better names.

Not as clear as Lotus 1-2-3 because the “intensiional definitions” threw me. After a bit of thinking, I realized that I could create really useful, clear, high impact words and phrases like:

  • artificial intelligence
  • Big Data
  • cognitive computing
  • concept search
  • data lake
  • metadata
  • natural language

That is outstanding.

Stephen E Arnold, January 21, 2016

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