Composite Software: From Search to Data Virtualization

January 30, 2017

I was deleting some of the old enterprise search and content processing data I had gathered over the years. I came across a text file which noted that Cisco Systems bought Composite Software in 2013. My recollection was that I had a screen shot of Composite’s search and retrieval interface. I dug around and located this graphic:

screen shot

Composite was founded in 2008, and at that time it was positioning its technology as an enterprise search solution. I was no longer compiling information for my Enterprise Search Report, which had devolved to a content management type outfit.

I did have in my files this diagram of what Composite’s search system morphed into:

image

Search is still in the architecture but it is called a Query Engine and includes traditional search functions; for example, a federation component, rules (which are very expensive to maintain in my experience), metadata, and editorial management now called “Governance.”

What’s interesting to me is that Composite figured out that search was not exactly a booming business. The company wrapped itself in next-generation features like Discovery and an Endeca-type “Studio” to create interfaces.

The sale of the company as a “data virtualization” vendor to Cisco took place in July 2013. According to a ZDNet write up, Cisco paid about $180 million for the five year old company. What I found interesting was the description of Composite in “

Composite provides software that connects different kinds of data on a network, including cloud and big data sources, and consolidates it as if it were in one place. In doing so, it allows companies to better visualize their data in order to make more accurate real-time decisions.

One would not know that Composite was an enterprise search vendor which pulled of a successful repositioning. Then Composite was able to sell the company to Cisco Systems, which had dabbled in search before this deal went down. At one time, I thought that Cisco would embrace open source search software.

Net net: Cisco got a search system for a fraction of the price HP paid for Autonomy. Composite is one of a small number of search vendors able to recognize the dead end that plain old search became. That’s important because slapping the word “semantic” on a keyword search system and shopping for a buyer may not be very productive.

In fact, it raises the question, “Why are some enterprise search vendors still pitching search?” Composite’s approach suggests that there are other ways to package keyword search and add some sizzle to what otherwise may be a cold chunk of stew meat.

Stephen E Arnold, January 30, 2017

IBM Watson: Inventing a Distilled Rum

January 29, 2017

I think this write up has some drops of truth in it. I wanted to check with a former MADD volunteer, but the email address wobbled and then fell against a light pole. The title was arresting: “IBM Watson Bottles ‘Holiday Spirit’ with New RUM Created Using Artificial Intelligence.” The source? The “real” news outfit the UK Mirror.

The write up explained that Watson allegedly “produces beverage based on social media posts.” I learned:

“Holiday Spirit” is claimed to be the world’s very first data-distilled rum and was created using IBM Watson. The supercomputer analyzed data from social media posts in order to produce a bespoke rum “that tastes like a holiday”. “In just six hours Watson was able to read 15 million posts on Facebook, Instagram and Twitter relating to holidays – and find the predominant emotions and concepts in those posts,” explained Joe Harrods, big data analyst and AI expert, who works closely with Watson.

The idea was that Watson guzzled 5,000 rum reviews. Then Watson demonstrated that it was in control of its faculties by “matching emotions from the reviews with ingredients.” Finally Walked a straight line to a master blender who concocted liquor, hooch, booze, or nectar that

has a subtle vanilla flavor, medium sweetness, hints of coconut and is naturally caressed with cinnamon and allspice.

So what? Here’s the results of the breathalyzer test:

“There’s no reason that this ‘taste sensation’ couldn’t be recreated for all kinds of experiences and emotions. We’ve already seen robot bartenders that can mix custom cocktails for every different punter based on their personality…

I am delighted that I have never had a drink of alcohol. I wonder if the same might be said of Watson or possibly the marketer who blended this knock out punch for artificial intelligence. What was that question? Oh, right. I remember: “Watson, when will you generate enough money to make IBM stakeholders happy.”

After 10 consecutive quarters of declining revenue, Holiday Spirit may be in short supply.

Stephen E Arnold, January 29, 2017

Semantic Search and Old Style Marketing

January 27, 2017

I read “It Used to Be So Easy to Get Google to Love You Now Not So Much.” I find it amusing that marketing methods which are ineffectual are still used in Google’s mobile oriented, buy-ad world. Here’s a great example from a small company trying to become a headliner.

Years ago I worked on a US government project. I developed a system which manipulated certain Web search systems’ indexing. It seems to me that one outfit has tried to emulate the DNA of my method. You can see the example of content marketing which is designed to polish a halo for a company involved in indexing. Yep, I know indexing is not exactly what makes the venture capitalists’ heart pound. But indexing has a long tradition of being

  1. Expensive
  2. Labor intensive if one wants to deliver precision and recall in search results
  3. Intellectually demanding, particularly when smart software goes off the rails so often
  4. Tough to make magnetic.

The write up “Searching with Semantic Technology” summarizes a write up in a “thought leader” publication. There is a parental reminder to remember how important indexing is. There is a concluding statement which explains that natural language processing plays a role in delivering search results. The buzzword “semantic” is repeated.

The only hitch in the git along is that the effort to trigger a Web search system using this abstract, keyword, and allegedly critical comment is that it is old and no longer works very well.

Why? Let me point out:

  1. Queries come from mobile device users. Some topics don’t lend themselves to mobile methods. It follows that methods based in whole or in part on the methods I developed and explained in my articles over the years are a bit like multiple Xerox copies of an original document. Faded and often useless.
  2. The jargon problem plagues those with niche capabilities. I pointed out in my cacaphone write up and compilation of buzzwords that most folks don’t have a clue what words mean. A good example is “semantic,” a term which has been devalued and applied to everything from marketing search engines to metasearch engines and more.
  3. The Web indexing systems have shifted over the years from reliance of a handful of proven indexing methods to wrappers of code which act “smart.” Results lists are essentially unpredictable today. Spoofing with words is a bit like shooting a handgun at the ocean in the hope of killing a fish.

For more information on an old system which doesn’t work very well anymore, navigate to www.augmentext.com. For more examples of marketing material which uses an ineffectual method to add razzle dazzle to a capability which is at best boring and more often of minimal interest, read the blog which serves as the home to this “insight.”

Kenny Toth, January 27, 2017

Looking for Insight and Universal Search: Dip in the Insightpool

January 26, 2017

I read “Insightpool Launches World’s Largest Influencer Search Engine.” I think I know what an influencer is. That is a person to whom others turn for guidance, insight, a phone call, or invitations to parties. I also know what an “influence peddler” is. That’s a person who delivers introductions, pressure, content marketing in various forms, and maybe for enough cash a good word to a really important person.

How does one find these folks? Easy. Use the University search system for influencers.

I learned:

With Universal Search, brand marketers can search for influencers across 100 social networks including Facebook, Twitter, Instagram, LinkedIn and other niche social communities such as Yelp!, Reddit, and Weibo. Additionally, they can view key insights by influencer segment to understand follower size and reach, conversation sentiment, frequency of activity and other characteristics. Marketers not only save significant time in selecting the right influencer, but also gain more detailed information about the influencers most likely to actively engage in their strategic campaigns. This leads to higher performance and conversions.

Okay. This is slightly different from getting a meeting with a senator’s administrative aide or wrangling a face to face with one of Google’s vice presidents of engineering.

The top influencer at Insightpool said:

“This is the largest influencer database on the planet. Other influencer platforms offer fewer than 100,000 at most. The real benefit with Universal Search lies in its pure simplicity — using a familiar search bar to find the most relevant influencers. It used to take days to identify the right people for a campaign. Now it takes seconds.”

You can run your queries using the “influencer marketing platform.” Tap into a search system that

blends together our mission of connecting brands and people on social media. We are not just an intelligent Influencer Marketing platform, we are not just a tech company, we are creators and innovators dedicated to revolutionizing the way brands build relationships and create measurable results through social channels. Since inception in 2013, our customers have helped refine the product roadmap, which has dramatically expanded to pioneering concepts such as identification, prediction, automated social drip marketing campaigns, nurturing and creating measurable insights that give brands results and revenue.

There you go. A search engine for those who want real information.

Stephen E Arnold, January 26, 2017

The SEO, PPC Baloney Sandwich: Total Search Can Be Dangerous

January 25, 2017

I love the clever folks’ ability to make language do tricks. I read “Unleashing the Potential of ‘Total’ Search.” The write up itself strikes me as a bit of content marketing. The objective is to whip up enthusiasm for a Breakfast Briefing “event.” I am okay with PR. I am not okay with taking a nifty word like search and morphing it into one of those online advertising concepts which confuse and lure the unwary.

image

The SEO and PPC baloney dog. It can be your pal and your meal ticket… if someone bites.

Total search, according to the write up, is “a holistic approach to search marketing which considers SEO [search engine optimization, that old relevance killer] and PPC [pay for click, that buy traffic approach pioneered by GoTo.com years ago] as a single channel.”

Search has a slightly different meaning to some folks here in down home rural Kentucky. Dictionary.com offers this definition:

1. to go or look through (a place, area, etc.)carefully in order to find something missing or lost:

They searched the woods for the missing child. I searched the desk for the letter.

2. to look at or examine (a person, object, etc.)carefully in order to find something concealed:

He searched the vase for signs of a crack. The police searched the suspect for weapons.

3. to explore or examine in order to discover:

They searched the hills for gold.

4. to look at, read, or examine (a record, writing,collection, repository, etc.) for information:

to search a property title; He searched the courthouse for a record of the deed to the land.

TheFreeDictionary.com says:

1. To move around in, go through, or look through in an effort to find something: searched the room for her missing earring; searched the desk for a pen.

2. To make a careful examination or investigation of; probe: search one’s conscience for the right thing to do.

3. Law To examine (a person or property) for the purpose of discovering evidence of a crime.

Verb transitive

1. To search a place or space in order to find something: searched all afternoon for my wallet.

2. To make a careful examination or investigation: searching for the right words to say.

3. Law To make a search for evidence.

noun

1. An act of searching.

2. Law The examination of a person or property, as by a law enforcement officer, for the purpose of discovering evidence of a crime.

3. A control mechanism on an audio or video player that rapidly advances or reverses the playing of a recording.

I suppose the inclusion of the word “total” allows the word search to become so much more to the wizard who is defining “total search” as marketing and ad buys.

The “total search” write up explains that “We live in a C2B world.” That means, I believe, “consumer to business world.”

Sorry. I don’t live in that world. I live in a world in which finding specific information, determining which information is either accurate or reasonably credible, and then analyzing that information in an effort to become more informed is important.

Presenting off point, inaccurate information is not my cup of tea.

How does one deliver “total search”? Here’s the “answer”:

There are several ways that a brand can realize the full potential of this approach. Some are fairly simple to implement, such as combining keyword research or aligning landing page testing. These can be merged into a single stream of work by your internal teams or agencies and will lead to immediate returns. Others (unifying leadership and introducing one search objective, for example) are likely to be more involved and may require a radical step-change in your organizational structure, driven from the top down. There are many other ways, which, in combination, can bring more benefits than the sum of the individual parts and drive significant incremental gains. Those brands that embrace a Total Search approach will be the ones that will more frequently be able to solve consumers’ problems and ultimately emerge successful.

There you go.

Think about this type of “search” in these three contexts:

  1. Your child is ill. One of the medical researchers at the hospital where doctors are trying to figure out how to address the disease presenting itself use “total search” to determine a course of action. Forget that baloney about precision and recall when searching the medical literature. Go for the content marketed drugs and the information delivered by an online ad. Care much about your child’s health? What’s your answer, gentle reader?
  2. You are involved in an accident. Three parties are involved, but only you have been injured. Your attorney is struggling to determine what coverage your automobile insurance provides. One of the other parties to the accident has decided to sue you even though your semi autonomous automobile was unable to avoid the collision caused by a vehicle hitting your car from behind. The momentum pushed your vehicle into a day care center van. Are you expecting your attorney to use free online Web search systems to locate legal information germane to your particular situation? How do you select your attorney? An ad supported online search?
  3. You are involved in a government project. You have to assemble information about a specific bad actor in a specific location. Your input will have a direct impact on the success or failure of the mission. This means that young men and women may die if you provide information that is not on point, accurate, and valid for that particular action. Are you prepared to rely on digital systems and content manipulated to get you to read information which is swizzled and promoted?

In each of these situations, the silliness and danger associated with “total search” becomes apparent to me. If you think that “total search” is just the ticket for you, you frighten me. A tainted baloney sandwich with slabs of SEO and PPC is not something too appealing to me. You can explain your preference to your ailing child, the attorney muffing your case, and the parents of the young woman who was killed due to your informational ignorance. Unleash your critical thinking, gentle reader.

Stephen E Arnold, January 25, 2017

OpenText Goes Cognitive

January 17, 2017

The Canadian roll up of ageing information access products has a new angle for 2017. No, it is not the OpenText “innovation” tour. No, it is not adding Alexa to its mind boggling array of content access systems such as BRS Search and IDI Information Dimension’s Basis. Not even the historical Fulcrum product gets an Alexa skill.

The future for OpenText is … a next generation cognitive platform.

Even more fascinating is that OpenText has had a Christine Maxwell moment and named the product Magellan. Who remembers the Magellan search and content access system? Ah, no one. I am not surprised. I met a millennial who had never used a camera with roll film yesterday.

If you want to know a bit more about the exciting old-new products, navigate to this OpenText page or follow  this link to a video. Yes, a video because OpenText is definitely in step with the next generation of enterprise software customers.

Stephen E Arnold, January 17, 2017

How Google Used Machine Learning and Loved It

January 16, 2017

If you use any search engine other than Google, except for DuckDuckGo, people cringe and doubt your Internet savvy.  Google has a reputation for being the most popular, reliable, and accurate search engine in the US.  It has earned this reputation, because, in many ways, it is the truth.  Google apparently has one upped itself, however, says Eco Consultancy in the article, “How Machine Learning Has Made Google Search Results More Relevant.”

In 2016, Google launched RankBrain to improve search relevancy in its results.  Searchmatics conducted a study and discovered that it worked.  RankBrain is an AI that uses machine learning to understand the context behind people’s search.  RankBrain learns the more it is used, similar to how a person learns to read.  A person learning to read might know a word, but can understand what it is based off context.

This increases Google’s semantic understanding, but so have the amount of words in a search query.  People are reverting to their natural wordiness and are not using as many keywords.  At the same time, back linking is not as important anymore, but the content quality is becoming more valuable for higher page rankings.  Bounce rates are increasing in the top twenty results, meaning that users are led to a more relevant result than pages with higher optimization.

RankBrain also shows Google’s growing reliance on AI:

With the introduction of RankBrain, there’s no doubt that Google is taking AI and machine learning more seriously.  According to CEO, Sundar Pichai, it is just the start. He recently commented that ‘be it search, ads, YouTube, or Play, you will see us — in a systematic way — apply machine learning in all these areas.’  Undoubtedly, it could shape more than just search in 2017.

While the search results are improving their relevancy, it spells bad news for marketers and SEO experts as their attempts to gain rankings are less effective.

Whitney Grace, January 16, 2016

RAVN Flaps Amidst a Flurry of Feathers

January 12, 2017

I read “Abraaj Drives Innovation in Private Equity Market with Implementation of RAVN’s Cognitive Search Solution.” The main idea is that RAVN, a vendor of enterprise search, has snagged a customer. That’s good. What’s interesting about the write up is the language of the “news.” Here’s a rundown of the words I highlighted as flaps of the RAVN’s marketing department wings:

  • Access
  • Artificial intelligence and AI
  • Classify
  • Cognitive search
  • Collaborate
  • Component
  • Connect enterprise
  • Data mining
  • Deal flow
  • Differentiation
  • Drive innovation
  • Dynamic decisions
  • Engagement
  • Engine as in “cognitive engine”
  • Experts and expertise
  • Extract
  • Functional knowledge
  • Ground breaking
  • Growth markets organization
  • Highly distributed network
  • Internal and external content
  • Intelligently transforms
  • Interrelationships
  • Knowledge graph
  • Knowledge management
  • Knowledge sources
  • Leverage
  • Lifecycle
  • Monitoring
  • Multi geography
  • Navigate
  • Phases
  • Platform
  • Proprietary
  • Sector knowledge.
  • Sectoral
  • Secure
  • Solutions
  • Teams
  • Transformation
  • Unstructured
  • Visualize

What’s left out? No analytics, which is one of the must have functions for a modern search and content processing system. My hunch is that RAVN has numbers in its nest. In the millennial editing frenzy, counting visitors and other useful items was overlooked. Amazing stuff. No wonder some folks roll their eyes when enterprise search vendors trot out keyword search dressed in rhetoric honed by Sophists.

For more lingo which makes search seem more than it is, review the list of cacaphones at this link. Ah, the cacophony of search and retrieval vendors.

Stephen E Arnold, January 12, 2017

Yahoo May Become Altaba

January 10, 2017

I read a US government filing which revealed that after Verizon allegedly buys the core assets of Yahoot. Sorry, I meant “Yahoo”, the remaining part of the Internet old timer will be called Altaba.

Image result for fred flintstone

Darn. I was hoping that the non core assets of Yahoot. Sorry, I meant Yahoo would have a more mellifluous name; for example:

  • Hooty
  • Marissa Ville
  • Yabba-dabba-doo.

My pick is “Yabba-dabba-doo” in a nice sans serif font. I would probably recall the new name as “Yabba-dabba-hoot.” As I age, my mind plays tricks on me. Kudos to the artist who designed a possible new logo for the company which should be named Yabba-dabba-hoo.

Stephen E Arnold, January 10, 2017

IBM and Its Five Year Vision: Nothing Like Vision Instead of Revenue

January 9, 2017

I read “IBM’s 5 Year Vision Focuses on New Technology for Visualizing the World.” The author is a Kevin Murnane who is the author of Nutrition for Cyclists: Eating and Drinking Before, During and After the Ride. Seems like excellent preparation for the low fat approach to IBM technology, doesn’t it?

The write up in the capitalist tool Forbes Magazine recycles information from “IBM 5 in 5. Five Innovations That Will Help Change Our Lives within Five Years: The Invisible Made Visible.” Now that’s a title designed for Web search engines.

The IBM write up identifies these technologies as life changers:

  1. Artificial intelligence like IBM Watson
  2. Superhero vision via “hyperimaging”
  3. Macroscopes
  4. Medical labs on a chip
  5. Smart sensors.

What I found interesting was this comment from the nutritionist:

People would be wise to listen when IBM talks about future technology. Their past achievements include the invention of floppy discs and hard drives, the relational database and SQL, Fortran, DRAM, the virtual machine, the ATM machine, magnetic stripe cards and the Universal Bar Code. Their employees have won five Nobel Prizes, six Turing Awards, ten National Medals of Technology, and five National Medals of Science. IBM has a long history of looking forward, thinking big and accomplishing what they set out to do. If their future is like their past, IBM’s 5 in 5 will be more than pie in the sky.

Unfortunately the Nobel Prizes, the Turing Awards, the National Medals for Technology and the five National Medals of Science are not translating to top line revenue growth and juicy profits for stakeholders. IBM’s vision does not include expanding aggressively the i2-type technology at a time when IBM Federal Systems might be in for a a bit of Gotham shock.

Give me that old fashioned revenue growth, please. I am not sure that macroscopes and superhero vision can change how I see the company’s last fifteen quarterly reports. One does not get fit on a low calorie revenue diet, does one?

Stephen E Arnold, January 9, 2017

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