Semantify Secures Second Funding Round
August 4, 2016
Data-management firm Semantify has secured more funding, we learn from “KGC Capital Invests in Semantify, Leaders in Cognitive Discovery and Analytics” at Benzinga. The write-up tells us primary investor KGC Capital was joined by KDWC Venture Fund and Bridge Investments in making the investment, as well as by existing investors (including its founder, Vishy Dasari.) The funds from this Series A funding round will be used to address increased delivery, distribution, and packaging needs.
The press release describes Semantify’s platform:
“Semantify automates connecting information in real time from multiple silos, and empowers non-technical users to independently gain relevant, contextual, and actionable insights using a free form and friction-free query interface, across both structured and unstructured content. With Semantify, there would be no need to depend on data experts to code queries and blend, curate, index and prepare data or to replicate data in a new database. A new generation self-service enterprise Ad-hoc discovery and analytics platform, it combines natural language processing (NLP), machine learning and advanced semantic modeling capabilities, in a single seamless proprietary platform. This makes it a pioneer in democratization of independent, on demand information access to potentially hundreds of millions of users in the enterprise and e-commerce world.”
Semantify cites their “fundamentally unique” approach to developing data-management technology as the force behind their rapid deployment cycles, low maintenance needs, and lowered costs. Formerly based in Delaware, the company is moving their headquarters to Chicago (where their investors are based). Semantify was founded in 2008. The company is also hiring; their About page declares, toward the bottom: “Growing fast. We need people;” as of this writing, they are seeking database/ BI experts, QA specialists, data scientists & knowledge modelers, business analysts, program & project managers, and team leads.
Cynthia Murrell, August 4, 2016
Sponsored by ArnoldIT.com, 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 ArnoldIT.com, publisher of the CyberOSINT monograph
IT Architecture Needs to Be More Seamless
August 14, 2015
IT architecture might appear to be the same across the board, but depending on the industry the standards change. Rupert Brown wrote “From BCBS to TOGAF: The Need For a Semantically Rigorous Business Architecture” for Bob’s Guide and he discusses how TOGAF is the defacto standard for global enterprise architecture. He explains that while TOGAF does have its strengths, it supports many weaknesses are its reliance on diagrams and using PowerPoint to make them.
Brown spends a large portion of the article stressing that information content and model are more important and a diagramed should only be rendered later. He goes on that as industries have advanced the tools have become more complex and it is very important for there to be a more universal approach IT architecture.
What is Brown’s supposed solution? Semantics!
“The mechanism used to join the dots is Semantics: all the documents that are the key artifacts that capture how a business operates and evolves are nowadays stored by default in Microsoft or Open Office equivalents as XML and can have semantic linkages embedded within them. The result is that no business document can be considered an island any more – everything must have a reason to exist.”
The reason that TOGAF has not been standardized using semantics is the lack of something to connect various architecture models together. A standardized XBRL language for financial and regulatory reporting would help get the process started, but the biggest problem will be people who make a decent living using PowerPoint (so he claims).
Brown calls for a global reporting standard for all industries, but that is a pie in the sky hope unless the government imposes regulations or all industries have a meeting of the minds. Why? The different industries do not always mesh, think engineering firms vs. a publishing house, and each has their own list of needs and concerns. Why not focus on getting industry standards for one industry rather than across the board?
Whitney Grace, August 14, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
IT Architecture Needs to Be More Seamless
August 7, 2015
IT architecture might appear to be the same across the board, but depending on the industry the standards change. Rupert Brown wrote “From BCBS To TOGAF: The Need For A Semantically Rigorous Business Architecture” for Bob’s Guide and he discusses how TOGAF is the defacto standard for global enterprise architecture. He explains that while TOGAF does have its strengths, it supports many weaknesses are its reliance on diagrams and using PowerPoint to make them.
Brown spends a large portion of the article stressing that information content and model are more important and a diagramed should only be rendered later. He goes on that as industries have advanced the tools have become more complex and it is very important for there to be a more universal approach IT architecture.
What is Brown’s supposed solution? Semantics!
“The mechanism used to join the dots is Semantics: all the documents that are the key artifacts that capture how a business operates and evolves are nowadays stored by default in Microsoft or Open Office equivalents as XML and can have semantic linkages embedded within them. The result is that no business document can be considered an island any more – everything must have a reason to exist.”
The reason that TOGAF has not been standardized using semantics is the lack of something to connect various architecture models together. A standardized XBRL language for financial and regulatory reporting would help get the process started, but the biggest problem will be people who make a decent living using PowerPoint (so he claims).
Brown calls for a global reporting standard for all industries, but that is a pie in the sky hope unless the government imposes regulations or all industries have a meeting of the minds. Why? The different industries do not always mesh, think engineering firms vs. a publishing house, and each has their own list of needs and concerns. Why not focus on getting industry standards for one industry rather than across the board?
Whitney Grace, August 7, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Connecting SharePoint with External Data
July 28, 2015
One of the most frequently discussed SharePoint struggles is integrating SharePoint data with existing external data. IT Business Edge has compiled a short slideshow with helpful tips regarding integration, including the possible use of business connectivity services. See all the details in their presentation, “Eight Steps to Connect Office 365/SharePoint Online with External Data.”
The summary states:
“According to Mario Spies, senior strategic consultant at AvePoint, a lot of companies are in the process of moving their SharePoint content from on-premise to Office 365 / SharePoint Online, using tools such as DocAve Migrator from SharePoint 2010 or DocAve Content Manager from SharePoint 2013. In most of these projects, the question arises about how to handle SharePoint external lists connected to data using BDC. The good news is that SharePoint Online also supports Business Connectivity Services.”
To continue to learn more about the tips and tricks of SharePoint connectivity, stay tuned to ArnoldIT.com, particularly the SharePoint feed. Stephen E. Arnold is a lifelong leader in all things search, and his expertise is especially helpful for SharePoint. Users will continue to be interested in data migration and integration, and how things may be easier with the SharePoint 2016 update coming soon.
Emily Rae Aldridge, July 28, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Expert Systems Acquires TEMIS
June 22, 2015
In a move to improve its product offerings, Expert System acquired TEMIS. The two companies will combine their assets to create a leading semantic provider for cognitive computing. Reuters described the acquisition in very sparse details: “Expert System Signs Agreement To Acquire French TEMIS SA.”
Reuters describes the merger as:
“Reported on Wednesday that it [Expert System] signed binding agreement to buy 100 percent of TEMIS SA, a French company offering solutions in text analytics
- Deal value is 12 million euros ($13.13 million)”
TEMIS creates technology that helps organizations leverage, manage, and structure their unstructured information assets. It is best known for Luxid, which identifies and extracts information to semantically enrich content with domain-specific metadata.
Expert System, on the other hand, is another semantically inclined company and its flagship product is Cogito. The Cogito software is designed to understand content within unstructured text, systems, and analytics. The goal is give organizations a complete picture of your information, because Cogitio actually understand what is processing.
TEMIS and Expert System have similar goals to make unstructured data useful to organizations. Other than the actual acquisition deal, details on how Expert System plans to use TEMIS have not been revealed. Expert System, of course, plans to use TEMIS to improve its own semantic technology and increase revenue. Both companies are pleased at the acquisition, but if you consider other buy outs in recent times the cost to Expert System is very modest. Thirteen million dollars underscores the valuation of other text analysis companies. Other text analysis companies would definitely cost more than TEMIS.
Whitney Grace, June 22, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Developing an NLP Semantic Search
May 15, 2015
Can you imagine a natural language processing semantic search engine? It would be a lovely tool to use in your daily routines and make research a bit easier. If you are working on such a project and are making a progress, keep at that startup because this is lucrative field at the moment. Over at Stack Overflow, an entrepreneuring spirit is trying to develop a “Semantic Search With NLP And Elasticsearch”:
“I am experimenting with Elasticsearch as a search server and my task is to build a “semantic” search functionality. From a short text phrase like “I have a burst pipe” the system should infer that the user is searching for a plumber and return all plumbers indexed in Elasticsearch.
Can that be done directly in a search server like Elasticsearch or do I have to use a natural language processing (NLP) tool like e.g. Maui Indexer. What is the exact terminology for my task at hand, text classification? Though the given text is very short as it is a search phrase.”
Given that this question was asked about three years ago, a lot has been done not only with Elasticsearch, but also NLP. Search is moving towards a more organic experience, but accuracy is often muddled by different factors. These include the quality of the technology, classification, taxonomies, ads in results, and even keywords (still!).
NLP semantic search is closer now than it was three years ago, but technology companies would invest a lot of money in a startup that can bridge the gap between natural language and machine learning.
Whitney Grace, May 15, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
The Philosophy of Semantic Search
May 13, 2015
The article Taking Advantage of Semantic Search NOW: Understanding Semiotics, Signs, & Schema on Lunametrics delves into semantics on a philosophical and linguistic level as well as in regards to business. He goes through the emergence of semantic search beginning with Ray Kurzweil’s interest in machine learning meaning as opposed to simpler keyword search. In order to fully grasp this concept, the author of the article provides a brief refresher on Saussure’s semantics.
“a Sign is comprised of a signifier, or the name of a thing, and the signified, what that thing represents… Say you sell iPad accessories. “iPad case” is your signifier, or keyword in search marketing speak. We’ve abused the signifier to the utmost over the years, stuffing it onto pages, calculating its density with text tools, jamming it into title tags, in part because we were speaking to robot who read at a 3-year-old level.”
In order to create meaning, we must go beyond even just the addition of price tag and picture to create a sign. The article suggests the need for schema, in the addition of some indication of whom and what the thing is for. The author, Michael Bartholow, has a background in linguistics and marketing and search engine optimization. His article ends with the question of when linguists, philosophers and humanists will be invited into the conversation with businesses, perhaps making him a true visionary in a field populated by data engineers with tunnel-vision.
Chelsea Kerwin, May 13, 2014
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Cerebrant Discovery Platform from Content Analyst
April 29, 2015
A new content analysis platform boasts the ability to find “non-obvious” relationships within unstructured data, we learn from a write-up hosted at PRWeb, “Content Analyst Announces Cerebrant, a Revolutionary SaaS Discovery Platform to Provide Rapid Insight into Big Content.” The press release explains what makes Cerebrant special:
“Users can identify and select disparate collections of public and premium unstructured content such as scientific research papers, industry reports, syndicated research, news, Wikipedia and other internal and external repositories.
“Unlike alternative solutions, Cerebrant is not dependent upon Boolean search strings, exhaustive taxonomies, or word libraries since it leverages the power of the company’s proprietary Latent Semantic Indexing (LSI)-based learning engine. Users simply take a selection of text ranging from a short phrase, sentence, paragraph, or entire document and Cerebrant identifies and ranks the most conceptually related documents, articles and terms across the selected content sets ranging from tens of thousands to millions of text items.”
We’re told that Cerebrant is based on the company’s prominent CAAT machine learning engine. The write-up also notes that the platform is cloud-based, making it easy to implement and use. Content Analyst launched in 2004, and is based in Reston, Virginia, near Washington, DC. They also happen to be hiring, in case anyone here is interested.
Cynthia Murrell, April 29, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Attensity’s Semantic Annotation Tool “Understands” Emoticons
April 27, 2015
The article on PCWorld titled For Attensity’s BI Parsing Tool, Emoticons Are No Problem explains the recent attempts at fine-tuning the monitoring and relaying the conversations about a particular organization or enterprise. The amount of data that must be waded through is massive, and littered with non-traditional grammar, language and symbols. Luminoso is one company interested in aiding companies with their Compass tool, in addition to Attensity. The article says,
“Attensity’s Semantic Annotation natural-language processing tool… Rather than relying on traditional keyword-based approaches to assessing sentiment and deriving meaning… takes a more flexible natural-language approach. By combining and analyzing the linguistic structure of words and the relationship between a sentence’s subject, action and object, it’s designed to decipher and surface the sentiment and themes underlying many kinds of common language—even when there are variations in grammatical or linguistic expression, emoticons, synonyms and polysemies.”
The article does not explain how exactly Attensity’s product works, only that it can somehow “understand” emoticons. This seems like an odd term though, and most likely actually refers to a process of looking it up from a list rather than actually being able to “read” it. At any rate, Attensity promises that their tool will save in hundreds of human work hours.
Chelsea Kerwin, April 27, 2014
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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