Beyond Intranet Search
October 28, 2014
Apparently, there is a difference between search and knowledge management; I guess you learn something new every day. CMS Wire asks, “Intranet Search: Where Documents Go to Die or KM Enabler?” Writer Jed Cawthorne uses Coveo’s platform to illustrate ways a company can go beyond the “baked in” search functionality in an intranet content management system. He writes:
“You don’t need to stick with the ‘built in solution’ if search is important to your KM / Enterprise Information Management strategies. There are alternatives beyond the ever more standard SharePoint (even though building FAST technology into core SharePoint 2013 has improved it) or the really big (and expensive) heavy hitters like HP’s IDOL platform.
“With the growing rate at which our mountains of internal content grow ever bigger, search capabilities are a fundamental element of an intranet, and of the broader digital workplace. If you want to apply long tail principles to mountains of social content, such as discussion forums, news feeds and updates, a search engine with concept search capabilities would be a good idea, unless you have a work force which is truly at one with tagging absolutely everything with appropriate and valuable metadata … (what, you work in the Library of the Jedi Temple? Cool!).”
Cawthorne spoke to Coveo’s Diane Berry about her company’s knowledge management options. She emphasizes broad content-source connectivity, metadata enrichment through text analytics (for companies lacking Jedi librarians), and building taxonomies through entity extraction. A user-interface based on users’ needs is also key, she notes, and mobile interfaces are a part of that. So is making it easy to adjust search and analysis parameters. See the write-up for more details and some screenshots that illustrate these points.
Cynthia Murrell, October 28, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
SharePoint Cumulative Updates Released
October 28, 2014
It is time for another round of cumulative updates for SharePoint, and this time they have been released without a mini-service pack. It is a recent shift and administrators may be left wondering how to deal with the change. Redmond Magazine covers all the details in their latest article, “Microsoft Releases October SharePoint Cumulative Updates.”
Their reporting begins:
“Microsoft released October cumulative updates (CUs) for both SharePoint 2010 and SharePoint 2013 this week, with lots of caveats. The October CUs are arriving this time without an ‘uber package,’ which is Microsoft’s term for a ‘mini-service pack.’ The absence of an uber package means that IT pros have to ensure that SharePoint farms are already updated with the September CU fixes before applying the October ones.”
Customers who are confused by the shift away from a cumulative package should continue reading the article for specific instructions based on your organization’s version of SharePoint. And for all the latest news, tips, and tricks regarding SharePoint, keep an eye on Stephen E. Arnold. He has made a career out of following all things search, and reporting on them on ArnoldIT.com. His SharePoint feed is particularly helpful for SharePoint users and administrators.
Emily Rae Aldridge, October 28, 2014
Enterprise Search, Knowledge Management, & Customer Service: Some of the Study Stuff Ups Evident?
October 27, 2014
One of my two or three readers sent me a link to “The 10 Stuff Ups We All Make When Interpreting Research.” The article walks through some common weaknesses individuals make when “interpreting research.” I don’t agree with the “all” in the title.
This article arrived as I was reading a recent study about search. As an exercise on a surprisingly balmy Sunday afternoon in Kentucky, I jotted down the 10 “stuff ups” presented in the Interpreting Research article. Here they are in my words, paraphrased to sidestep plagiarism, copyright, and Google duplication finder issues:
- One study, not a series of studies. In short, an anomaly report.
- One person’s notion of what is significant may be irrelevant.
- Mixing up risk and the Statistics 101 notion of “number needed to treat” gets the cart before the horse.
- Trends may not be linear.
- Humans find what they want to find; that is, pre existing bias or cooking the study.
- Ignore the basics and layer cake the jargon.
- Numbers often require context. Context in the form of quotes in one on one interviews require numbers.
- Models and frameworks do not match reality; that is, a construct is not what is.
- Specific situations do matter.
- Inputs from colleagues may not identify certain study flaws.
To test the article’s premises, I I turned to a study sent to me by a persona named Alisa Lipzen. Its title is “The State of Knowledge Management: 2014. Growing role & Value of Unified Search in Customer Service.” (If the link does not work for you, you will have to contact either of the sponsors, the Technology Services Industry Association or Coveo, an enterprise search vendor based in Canada.) You may have to pay for the report. My copy was free. Let’s do a quick pass through the document to see if it avoids the “stuff ups.”
First, the scope of the report is broad:
1. Knowledge management. Although I write a regular column for KMWorld, I must admit that I am not able to define exactly what this concept means. Like many information access buzzwords, the shotgun marriage of “knowledge” and “management” glues together two abstractions. In most usages, knowledge management refers to figuring out what a person “knows” and making that information available to others in an organization. After all, when a person quits, having access to that person’s “knowledge” has a value. But “knowledge” is as difficult to nail down as “management.” I suppose one knows it when one encounters it.
2. Unified search. The second subject is “unified search.” This is the idea that a person can use a single system to locate information germane to a query from a single search box. Unified suggests that widely disparate types of information are presented in a useful manner. For me, the fact that Google, arguably the best resourced information access company, has been unable to deliver unified search. Note that Google calls its goal “universal search.” In the 1980s, Fulcrum Technologies (Ottawa, Canada) search offered a version of federated search. In 2014, Google requires that a user run a query across different silos of information; for example, if I require informatio0n about NGFW I have to run the query across Google’s Web index, Google scholarly articles, Google videos, Google books, Google blogs, and Google news. This is not very universal. Most “unified” search solutions are marketing razzle dazzle for financial, legal, technical, and other reasons. Therefore, organizations have to have different search systems.
3. Customer service. This is a popular bit of jargon. The meaning of customer service, for me, boils down to cost savings. Few companies have the appetite to pay for expensive humans to deal with the problems paying customers experience. Last week, I spent one hour on hold with an outfit called Wellcare. The insurance company’s automated system reassured me that my call was important. The call was never answered. What did I learn. Neither my call nor my status as a customer was important. Most information access systems applied to “customer service” are designed to drive the cost of support and service as low as possible.
“Get rid of these expensive humans,” says the MBA. “I want my annual bonus.”
I was not familiar with the TSIA. What is its mission? According the the group’s Web site:
TSIA is organized around six major service disciplines that address the major service businesses found in a typical technology company.
Each service discipline has its own membership community led by a seasoned research executive. Additionally, each service discipline has the following:
- Focused research agenda
- Dedicated research team
- Benchmark study
- Dedicated track at Technology Services World conferences
- Member Advisory Board
In addition, we have a research practice on Service Technology that spans across all service discipline focus areas.
My take is that TSIA is a marketing-oriented organization for its paying members.
Now let’s look at some of the the report’s key findings:
The people, process, and technology components of technology service knowledge management (KM) programs. This year’s survey examined core metrics and practices related to knowledge capture, sharing, and maintenance, as well as forward-looking elements such as video, crowd sourcing, and expertise management. KM is no longer just of interest to technical support and call centers. The survey was open to all TSIA disciplines, and 50% of the 400-plus responses were from groups other than support services, including 24% of responses from professional services organizations.
Connotate on the Importance of a Data Supply Chain
October 27, 2014
Here’s a new spin on scraping and parsing from Connotate’s blog, Web Data Insider. The recent emphasis on predictive analytics has writer Laura Teller discussing “The Data Supply Chain… and Why You Should Get One.” She reminds us that businesses now do much more with data than they used to. In fact, she asserts, any company that invests in data analytics possesses a critical advantage. Of course, as a prominent web-data extraction firm, Connotate does have a dog in this fight; at the same time, Teller has a point—for many businesses, especially larger ones, data analytics can be an indispensable tool.
Companies put considerable effort into streamlining their supply chains for other resources, so why not data? The article elaborates, and gives us a checklist for investigating our own data-supply needs:
“Once we start conceiving of data as a critical input or a brave new resource, it changes the paradigm of how we think about it, manage it, and leverage it. Data is no longer just an artifact of the ‘real work’ of companies. Rather, it’s something that has to be strategically sourced, managed, and leveraged. Just as companies have supply chains for other raw materials, like sugar, steel, electronic components, etc., they have to think about data in the same way and with the same rigor. They have many decisions to make:
*What to get and where they’ll get it
*How to ensure supply
*How to protect their ability to get it
*Who they’ll source from and how they’ll manage them
*What to pay for it
*How to store it
*How to refine it and add value to it
*How to package it for sale”
Teller notes that her company welcomes this “paradigm shift,” which is no surprise, considering that they are well-positioned to help customers address this burgeoning need. The company’s platform has been named a KMWorld “Trend-Setting Product” a healthy nine times. Based in New Brunswick, New Jersey, Connotate was founded in 2000.
Cynthia Murrell, October 27, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Living with Google Requires Innovation
October 27, 2014
The article on South China Morning Post Technology titled Search Websites Diversify in Scope and Learn to Coexist with Google explores the options for Google’s ugly stepsisters Bing and Yahoo (among others). Rather than even attempting to unseat the search giant, Chris Wallace of Mindshare Worldwide and Will McInnes of Brandwatch advocate a tailoring approach for search engines not named Google. The article states,
“Microsoft has Xbox, and this is its opportunity to integrate into the living room and be the search device of choice there” Wallace says… niche search engines are emerging, usually with one killer app that does something specific Google can’t match. None will take over from the Big G any time soon, but if you have a specific need, they’re worth bearing in mind… The message? Don’t avoid Google, but diversify your usage.”
Whether you are looking specifically for music, social media data, or the latest news, there are alternatives to Google in the form of Live Plasma, Blekko and Pinterest or even Facebook. The article suggests loosening the Google security blanket we have wrapped ourselves in so cozily and considering other options. Specialized search engines like Yelp for restaurants will help us more because they are tailor-made for one area of the market.
Chelsea Kerwin, October 27, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Semantic Web: Remember That for Enterprise Search?
October 26, 2014
You can find an interesting discussion of the Semantic Web on Hacker News. Semantic Web search engines have had a difficult time capturing the imagination of the public. The write up and the comments advance the notion that the Semantic Web is alive and well, just invisible.
I found the statement from super Googler Peter Norvig a window into how Google views the Semantic Web. Here’s the snippet:
Peter Norvig put it best: “The semantic web is the future of the web, and always will be.” (For what it’s worth, the startup school video that quote comes from is worth watching: http://youtu.be/LNjJTgXujno?t=20m57s)
There are references to “semantic search” companies that have failed; for example, Ontoprise. There are links to clever cartoons.
The statement I highlighted was:
The underlying data just doesn’t necessarily map very well into the seem-web representations, so duplicates occur and possible values explode in their number of valid permutations even though they all mean the same handful of things. And it’s the read-only semantic-web, so you can’t just clean it, you have to map it.. Which is why I’m always amazed that http://www.wolframalpha.com/ works at all. And hopefully one day https://www.freebase.com/ will be a thing. I remember being excited about http://openrefine.org/ for “liberating” messy data into clean linked data… but it turns out that you really don’t want to curate your information “in the graph”; it seems obvious, but traditional relational datasets are infinitely more manageable than arbitrarily connected nodes in a graph. So, most CMS platforms are doing somewhat useful things in marking up their content in machine-readable ways (RDFa, schema.org [as evil as that debacle was], HTTP content-type negotiation and so on) either out-of-the-box or with trivially installed plugins.
Ah, content management systems. Now that’s the model for successful information access as long as one does not want engineering drawings, videos, audio, binaries, and a host of proprietary data types like i2 Analyst Notebook files.
Worth checking out the thread in my view.
Stephen E Arnold, October 26, 2014
ArnoldIT Search Requirements Video
October 26, 2014
The goslings continue to experiment with short videos. The most recent on is about enterprise search requirements. The four minute YouTube program hits some highlights about the perilous process of licensing an enterprise search system. The video is located at http://bit.ly/1qx87yr.
Donald C Anderson, October 26, 2014
Google and Search: Hey, Mobile, Mobile, Mobile
October 25, 2014
I read “Google’s Head of Android to Oversee Its Most Important Products.” Interesting news. Larry Page is moving on up. For me, search is moving on down. Here’s the passage I highlighted:
The promotion punctuates Pichai’s quick rise inside the company as well as CEO Larry Page’s desire to focus on off-loading some of his management duties to better focus on overall business strategy. While Google’s search and advertising business still generates $50 billion a year in revenue, some financial analysts fear its business is slowing. The company last week reported that paid clicks for the third quarter rose 17 percent from the same period last year. That compares with 26 percent growth the year before.
My view is that search is the loser in this deal. Mr. Brin is chasing balloons and solving death. Mr. Page wants to think about making money from a higher level.
The Google has change in neon lights in front of the dinosaur bones. Metaphor? You bet. You can research this with reasonable precision and recall on either Yandex.com or iseek.com. Google? Well, you get lots of ads on your desktop computer. On your mobile phone? Well, not too many ads fit on the tiny screen. Aye, that’s the problem, Captain.
Stephen E Arnold, October 25, 2014
If Amazon Is Not a Real Business, Can Amazon Deliver Real Search?
October 25, 2014
Interesting idea: Amazon is not a business. The story “Ex-Microsoft CEO Steve Ballmer Says Amazon Isn’t a Real Business” floats this idea. The argument is that Amazon does not make money. Let’s assume this notion is correct. Can an outfit that is not a real business deliver real search? The answer is, “Yep.” Dozens of search vendors have been living from hand to mouth for many years. Each of these companies would assert that they have state-of-the-art, supercalifragilisticexpialidocious technology.” But there’s the money thing, isn’t there. Hakia seems to be the most recent search vendor to go into slow down mode. Others are taking their foot of the gas pedal as well. There is some truth to the real businesses make money premise. Will Amazon deliver “real” search. Probably a long shot.
Stephen E Arnold, October 25, 2014
Looking for an AI Silver Bullet to Make Software Smart? Keep Looking
October 24, 2014
Here in Harrod’s Creek, Kentucky there is not too much chatter about machine learning. It is hunting season. Time to get out the Barrett Automatic Rifle and go hunting for varmints.
Sundown yesterday when calm returned to the hollow, I read “Machine-Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts.”
My thought after reading the IEEE article was that I was really tired of the artificial intelligence yap yap. Now a whiz at UCal Berkeley is pointing out that some of the methods are a “cartoon.”
The Dr. Michael Jordan says:
I think data analysis can deliver inferences at certain levels of quality. But we have to be clear about what levels of quality. We have to have error bars around all our predictions. That is something that’s missing in much of the current machine learning literature.,,if people use data and inferences they can make with the data without any concern about error bars, about heterogeneity, about noisy data, about the sampling pattern, about all the kinds of things that you have to be serious about if you’re an engineer and a statistician—then you will make lots of predictions, and there’s a good chance that you will occasionally solve some real interesting problems. But you will occasionally have some disastrously bad decisions. And you won’t know the difference a priori. You will just produce these outputs and hope for the best. And so that’s where we are currently.
In short, marketing hyperbole takes precedence over the plodding realities of the steps required of a person aspiring to a PhD in statistics is supposed to follow.
With regard to the applications that deliver predictive outputs, Dr. Jordan says:
But unless you’re actually doing the full-scale engineering statistical analysis to provide some error bars and quantify the errors, it’s gambling. It’s better than just gambling without data. That’s pure roulette. This is kind of partial roulette.
I strongly recommend you read the interview. I would not involve a search or content processing marketer in the exercise, however.
Stephen E Arnold, October 24, 2014
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