I2E Semantic Enrichment Unveiled by Linguamatics
July 21, 2014
The article titled Text Analytics Company Linguamatics Boosts Enterprise Search with Semantic Enrichment on MarketWatch discusses the launch of 12E Semantic Enrichment from Linguamatics. The new release allows for the mining of a variety of texts, from scientific literature to patents to social media. It promises faster, more relevant search for users. The article states,
“Enterprise search engines consume this enriched metadata to provide a faster, more effective search for users. I2E uses natural language processing (NLP) technology to find concepts in the right context, combined with a range of other strategies including application of ontologies, taxonomies, thesauri, rule-based pattern matching and disambiguation based on context. This allows enterprise search engines to gain a better understanding of documents in order to provide a richer search experience and increase findability, which enables users to spend less time on search.”
Whether they are spinning semantics for search, or if it is search spun for semantics, Linguamatics has made their technology available to tens of thousands of users of enterprise search. Representative John M. Brimacombe was straightforward in his comments about the disappointment surrounding enterprise search, but optimistic about 12E. It is currently being used by many top organizations, as well as the Food and Drug Administration.
Chelsea Kerwin, July 21, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
13 Career Jeopardizing Enterprise Search Issues
July 6, 2014
The ArnoldIT team has combed through our archive of enterprise search data. We have identified the top 13 surprises that enterprise search delivers to licensees. Get hit with several of these surprises and you might find yourself seeking a future in a different line of work.
13 Users don’t like the new system or the old system, for that matter. Dissatisfaction with enterprise search, regardless of vendor, runs at 55 to 70 percent. See Successful Enterprise Search Management at http://www.galatea.co.uk/index.php?option=com_content&task=view&id=35&Itemid=53
12 No one pays attention to search costs until the CFO conducts an audit. Cost overruns plague nine out of 10 enterprise search deployments. The reason is that a comprehensive compilation of costs is not part of an enterprise search deployment. When a system crashes, the costs for emergency and rush work comes from a different line item. Customization is usually taken from a different budget allocation. Consultants and contractors are paid from another budget allocation. When the costs are added up, everyone seems surprised at the money spent for a system few find satisfactory. The hunt for a scapegoat is on.
11 Open source search and proprietary search solutions differ little in costs. Aside from an initial licensing fee, the costs for customization, optimization, contractors, programming, and enhancement are essentially the same.
10 Many major enterprise search systems are now based on open source software. The reason is that the cost for the basic functions are rising and are difficult to control. Therefore, vendors use open source and concentrate on extra cost add ons.
9 Every enterprise search system struggles to process content without human intervention, additional “connectors,” extract transform load activities, and original scripting. When content cannot be acquired, the few who notice will squawk, often loudly.
8 Latency creates a problem because new or changed content imposes significant costs on the licensee to cope with the need to process content in near real time and then refresh the indexes whether these are state of the art in memory systems or old style spinning discs and cached methods. When a user asks, “Why is the system too slow?, it may be difficult to make improvements when budgets are constrained.
7 Modern systems include adds on that permit faceting, query expansion, and linguistic functions. Unless these are “tuned” by subject matter experts or analysts, the outputs can generate irrelevant or off-query outputs. The notion of “smart, automatic” search and retrieval are often chimera.
6 Users typically do not conduct a thorough, research librarian type of investigation of query results. Enterprise search systems that generate laundry lists of results that are stale or irrelevant will be used by the person running the query. The assumption that online systems are “correct” is held by 95 percent of an enterprise system’s users. Only when a user cannot find a document that is supposed to be in the search index will the user realize that the system is not working as assumed. If the issues arises during a crunch, the prudent search manager will polish that résumé.
5 Enterprise search scaling is expensive and complex. The idea that scaling is seamless and economical is false. Improving the “performance” of an enterprise search system requires correct identification of the particular factor or factors creating latency. More frequent updates may not be possible without re-engineering an enterprise search system’s infrastructure. How much has Google’s core method changed in 14 years? What about Amazon? What about Autonomy, Endeca, Lucene, etc.? The answer is, “Not too much.” Search is very, very complicated.
4 Interface does not improve precision and recall of a search system. Interface and cosmetic design changes are easy to talk about and “more fun” to work on that figuring out how to process content more quickly and update the searchable indexes in with significantly less latency. If users grouse, an interface change won’t silence the critics or slow the proliferation of bootleg systems in units that are dissatisfied with the search status quo.
3 Search with text mining functions often rely on standard methods and algorithm configurations that licensees cannot modify without specialist training. As a result, many systems output results that may be based on assumptions not germane to the licensee’s content. Hence, outputs purporting to provide insight into business intelligence or predictions may be incorrect. Search is not text mining. Search is not a Silver Bullet for Big Data. Search is pretty much type a query and get a laundry lists of stuff that must be reviewed by a human. Automatic reports are often off point.
2 Search appliances are not money savers. The Google Search Appliance costs as much as Autonomy or Endeca to deploy. The cloud is not the big money savers marketers want me to believe it is. Cloud search solutions reduce the need for capital expense, but the on going costs are comparable to on premises solutions. A search appliance may be like handcuffs. The cloud may be overly complicated. No highways leads to the Magic Kingdom for search. If you think search is a slam dunk, you are misinformed.
1 Enterprise search systems are more alike than different. The reason is that computational methods have not changed much since the first commercial systems became available in the late 1960s. The differences are created by marketing, not by significantly different numerical recipes. Most users cannot differentiate between or among systems. The concepts of precision and recall are unknown. Users believe that search systems are right almost all the time. Yikes.
Stephen E Arnold, July 6, 2014
Presentation by a NoSQL Leader
July 4, 2014
The purported father of NoSQL, Norman T. Kutemperor, made an appearance at this year’s Enterprise Search & Discovery conference, we learn from “Scientel Presented Advanced Big Data Content Management & Search With NoSQL DB at Enterprise Search Summit in NY on May 13” at IT Business Net. The press release states:
“Norman T. Kutemperor, President/CEO of Scientel, presented on Scientels Enterprise Content Management & Search System (ECMS) capabilities using Scientels Gensonix NoSQL DB on May 13 at the Enterprise Search & Discovery 2014 conference in NY. Mr. Kutemperor, who has been termed the Father of NoSQL, was quoted as saying, When it comes to Big Data, advanced content management and extremely efficient searchability and discovery are key to gaining a competitive edge. The presentation focused on: The Power of Content – More power in a NoSQL environment.”
According to the write-up, Kutemperor spoke about the growing need to manage multiple types of unstructured data within a scalable system, noting that users now expect drag-and-drop functionality. He also asserted that any NoSQL system should automatically extract text and build an index that can be searched by both keywords and sentences. Of course, no discussion of databases would be complete without a note about the importance of security, and Kutemperor emphasized that point as well.
The veteran info-tech company Scientel has been in business since 1977. These days, they focus on NoSQL database design; however, it should be noted that they also design and produce optimized, high-end servers to go with their enterprise Genosix platform. The company makes its home in Bingham Farms, Michigan.
Cynthia Murrell, July 04, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Enterprise Search Adoption Survey: More Shifting Sand
June 27, 2014
I read “Enterprise Search Adoption Remains Low: Survey.” On one hand the notion that most organizations have trouble finding email like the US Internal Revenue Service is a truism. On the other hand, enterprise search is one of the enterprise applications that promises everything and often disappoints a large percentage of users.
The write up asserts:
It asked 300 enterprise IT security professionals at two major security-themed industry events, and found that only 38% of IT departments have invested in or plan to invest in enterprise search capabilities for a range of reasons topped by security concerns. When asked to choose the biggest obstacle to enterprise search adoption, 68% cited the risk of employees locating and accessing files they should not have permission to view.
The article includes a quote from an outfit called Varonis and a plug for a product with which I am unfamiliar, DatAnswers. The full enterprise search study can be found at http://info.varonis.com/enterprise-search-report
Oh, and the sponsor of the study? Varonis and DatAnswers. Enterprise search is nothing if not consistent in its marketing efforts.
Stephen E Arnold, June 27, 2014
Predicting the Future of Search
June 27, 2014
Enterprise search dates back to the 1960s under IBM, but Google has definitely dictated the average user’s expectations regarding modern day information retrieval. So while the past is important, the future is uncertain and inquiring minds want to know what to expect. Docurated turns to the experts in their article, “Enterprise Search: 14 Industry Experts Predict the Future of Search.”
The article begins:
“We wanted to gain a clearer understanding of current state of the enterprise search industry. Given the steady evolution of enterprise search, we also wanted to gain some insight into what the future may hold. To do so, we gathered a select number of industry experts and asked two simple questions:
1. What is your assessment of today’s enterprise search industry?
2. What do you think the future of ‘search’ will look like?”
The results from the experts are mixed. Few think that the model will change dramatically though many do mention continued innovation in the areas of big data, open source, visual search, and others. And even if all the experts did agree, the future would still be uncertain. Those interested in the future of search should stay tuned in for the latest news as it hits, and just hold on for the ride.
Emily Rae Aldridge, June 27, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Enterprise Graph Search Changes the Retrieval Game
June 27, 2014
New models of information retrieval are emerging, taking the field away from the traditional keyword format. Facebook made quite a stir with its implementation of graph search, and now experts feel it may have implications for the enterprise. Read more in the Synata article, “Enterprise Graph Search: A Game Changer in Information Retrieval.”
The article begins:
“In Facebook Graph Search, results are based on both the content of the user and their friends’ profiles and the relationships between the user and their friends. They’re personalized for the individual user. But what does this have to do with the enterprise? . . . Because of today’s massively scalable infrastructure platforms, API ubiquity, and graph analysis capabilities, the rapid gains in query understanding and information retrieval techniques are about to have resounding implications for enterprise search.”
The graph model allows for extreme relevance, bringing all the floating connections together in a bigger picture, the graph. And while theorists are saying that this type of technology has huge implications, implementation has yet to be realized. Keep an eye out for the breakthrough of graph search. When it hits SharePoint it will have made the mainstream.
Emily Rae Aldridge, June 27, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Commonsense Conclusions from Azure Consultant
June 26, 2014
An azure chip consultant explains that enterprise search is just what the doctor ordered for big data; Gartner declares that “Enterprise Search Can Bring Big Data Within Reach.” Um, it seems that search is kind of implied in the term. What good are data and data analysis if there is no way to find and use the information? Actually, research director Darin Stewart is talking about gaining the benefits of big data without the cost and turmoil of “overhauling the data center,” which, apparently, some folks don’t understand is an option. He writes:
“Providing big data functionality without overhauling the data center is achievable with a two-pronged approach that combines augmented enterprise search and distributed computing. Search is very good at finding interesting things that are buried under mounds of information. Enterprise search can provide near-real-time access across a wide variety of content types that are managed in many otherwise siloed systems. It can also provide a flexible and intuitive interface for exploring that information. The weakness of a search-driven approach is the fact that a search application is only as good as the indexes upon which it is built….
“Distributed computing frameworks provide the environment necessary to create these indexes. They are particularly well-suited to efficiently collect extremely large volumes of unprocessed, individually low-value pieces of information and apply the complex analytics and operations that are necessary to transform them into a coherent and cohesive high-value collection. The ability to process numerous source records and apply multiple transformations in parallel dramatically reduces the time that is required to produce augmented indexes across large pools of information.”
The article goes on to point out that cloud-friendly open-source tools to support such a framework are readily available. Stewart shares a link to his Gartner document on the topic (registration required), and is scheduled to speak about it at Gartner’s Catalyst Europe conference, held in London in mid-June.
Cynthia Murrell, June 26, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Trying To Make A Search More Relevant
June 20, 2014
Here is a thought that does not make much sense when taken in the bigger picture scope. PRLog explains the conundrum in “BA Insight To Discuss How To Make Enterprise Search Relevant Through Unified Information Access.” BA Insight’s CTO Jeff Fried and David Schubmehl, a research director at IDC, will host a webinar that shares the same name as the above article. The webinar will discuss how enterprise search technology is lagging:
“Due to the vast explosion of structured and unstructured data, users are experiencing increasing challenges locating and accessing the critical information and expertise needed to excel in their roles. Even the enterprise search technology that has been implemented to resolve these issues is failing to locate relevant information while providing a sub-par user experience. This can have negative consequences, such as the inability to effectively respond to customer queries, widespread duplication of effort, and decreased employee productivity.”
Fried and Schubmehl will focus on how enterprise search is changing, how organizations are driving demand, and how to make enterprise search a killer application. The bigger question is if BA Insight is using this to make their own products more relevant? Has enterprise search really lost its relevancy or is it one observation? The “unified information access” tag is one used by other companies like Sinequa and Attivio. These companies appear to be cut from the same cloth when touting their talents.
Whitney Grace, June 20, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
New COO with Fast Roots for Attivio
May 9, 2014
When Microsoft snapped up Fast Search in 2008, the great minds behind the platform “scattered to the four winds,” as our own expert, Stephen E Arnold, put it back in 2012. Now, yet another Fast Search alum has joined Attivio, we learn from “Attivio Names Stephen Baker Chief Operating Officer” at Virtual-Strategy Magazine. Baker will serve as the company’s very first COO. The press release summarizes his background:
“Prior to joining Attivio, Baker was President and Chief Revenue Officer of RAMP, a SaaS-based Online Video Platform based in Boston. During his seven years at RAMP, Baker led the sales, account management and client operations teams to profitability and was an integral part of raising the company’s B and C rounds of funding.
“Baker previously worked under Riaz at FAST, first as Product Manager and VP of Business Development for the AllTheWeb Business unit, which was sold to Overture/Yahoo! in 2003, and later as VP/General Manager eBusiness for FAST’s enterprise software business. Baker also spent a year as CEO of Online for Reed Business Information, where he was instrumental in driving digital strategy, execution, and revenue growth.”
It does seem the position should be a good fit, and we wish Baker and Attivio well. Baker’s revenue background reminds us of the recent legal troubles for Fast Search founder John Lervik, who it seems will serve at least a year in prison for financial reporting issues. See here for Arnold’s analysis on why enterprise search is so difficult to manage financially (and technically.) I view it as a cautionary tale.
Cynthia Murrell, May 09, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
IBMs ICAwES Red Book Available
April 17, 2014
The article on IBM.com titled Building Enterprise Search Solutions Using IBM Content Analytics with Enterprise Search involves IBM rolling out information about ICAwES. That excellent acronym stands for IBM® Content Analytics with Enterprise Search, as you may have guessed. It allows for customized synonym dictionaries for search, annotators, and the integration of diverse kinds of repositories. The abstract explains,
“With ICAwES enterprise search solutions, you can integrate fields from multiple content repositories to create a single, integrated user search experience. In addition, the enterprise search solutions can use fields and facets in various ways to create diverse views of your search result set, thus helping you identify the hidden meaning of your unstructured content. This IBM Redbooks® Solution Guide explains, from a high level, how to build enterprise search solutions using ICAwES.”
A red book is available through IBM Redbooks. It offers information on using the “text classification capability”, the “LanguageWare Resource Workbench” and “IBM Content Assessment”. It is aimed at IT architects and business users interested in expanding their usage and improving customer satisfaction and business operations, all interesting information. The reference to the “billion dollar baby Watson” appears in the footer, but not in the explanation of the ICAwES.
Chelsea Kerwin, April 17, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
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