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Category: Enterprise search & search technology (Page 29 of 59)

Research, analysis, and news about enterprise search and search markets, technologies, practices, and strategies, such as semantic search, intranet collaboration and workplace, ecommerce and other applications.

Before we consolidated our blogs, industry veteran Lynda Moulton authored our popular enterprise search blog. This category includes all her posts and other enterprise search news and analysis. Lynda’s loyal readers can find all of Lynda’s posts collected here.

For older, long form reports, papers, and research on these topics see our Resources page.

In the Field: The Enterprise Search Market Offers CHOICES

Heading into the Gilbane Boston conference next month we have case studies that feature quite an array of enterprise search applications. So many of the search solutions now being deployed are implemented with a small or part-time staff that it is difficult to find the one or two people who can attend a conference to tell their stories. We have surveyed blogs, articles and case studies published elsewhere to identify organizations and people who have hands-on-experience in the trenches deploying search engines in their enterprises. Our speakers are those who were pleased to be invited and they will be sharing their experiences on December 3rd and 4th.

From search appliances Thunderstone and Google Search Appliance, to platform search solutions based on Oracle Secure Enterprise Search, and standalone search products Coveo, Exalead, and ISYS, we will hear from those who have been involved in selecting, implementing and deploying these solutions for enterprise use. From a Forrester industry analyst and Attivio developer we’ll hear about open source options and how they are influencing enterprise search development. The search sessions will be rounded out as we explore the influences and mergers of text mining, text analytics with Monash Research and semantic technologies (Lexalytics and InfoExtract) as they relate to other enterprise search options. There will be something for everyone in the sessions and in the exhibit hall.

Personally, I am hoping to see many in the audience who also have search stories within their own enterprises. Those who know me will attest to my strong belief in communities of practice and sharing. It strengthens the marketplace place when people from different types of organizations share their experiences trying to solve similar problems with different products. Revealing competitive differentiators among the numerous search products is something that pushes technology envelopes and makes for a more robust marketplace. Encouraging dialogue about products and in-the-field experiences is a priority for all sessions at the Gilbane Conference and I’ll be there to prompt discussion for all five search sessions. I hope you’ll join me in Boston.

Apples and Orangutans: Enterprise Search and Knowledge Management

This title by Mike Altendorf, in CIO Magazine, October 31, 2008, mystifies me, Search Will Outshine KM. I did a little poking around to discover who he is and found a similar statement by him back in September, Search is being implemented in enterprises as the new knowledge management and what’s coming down the line is the ability to mine the huge amount of untapped structured and unstructured data in the organisation.

Because I follow enterprise search for the Gilbane Group while maintaining a separate consulting practice in knowledge management, I am struggling with his conflation of the two terms or even the migration of one to the other. The search we talk about is a set of software technologies that retrieve content. I’m tired of the debate about the terminology “enterprise search” vs. “behind the firewall search.” I tell vendors and buyers that my focus is on software products supporting search executed within (or from outside looking in) the enterprise on content that originates from within the enterprise or that is collected by the enterprise. I don’t judge whether the product is for an exclusive domain, content type or audience, or whether it is deployed with the “intent” of finding and retrieving every last scrap of content lying around the enterprise. It never does nor will do the latter but if that is what an enterprise aspires to, theirs is a judgment call I might help them re-evaluate in consultation.

It is pretty clear that Mr. Altendorf is impressed with the potential for Fast and Microsoft so he knows they are firmly entrenched in the software business. But knowledge management (KM) is not now, nor has it ever been, a software product or even a suite of products. I will acknowledge that KM is a messy thing to talk about and the label means many things even to those of us who focus on it as a practice area. It clearly got derailed as a useful “discipline” of focus in the 90s when tool vendors decided to place their products into a new category called “knowledge management.”

It sounded so promising and useful, this idea of KM software that could just suck the brains out of experts and the business know-how of enterprises out of hidden and lurking content. We know better, we who try to refine the art of leveraging knowledge by assisting our clients with blending people and technology to establish workable business practices around knowledge assets. We bring together IT, business managers, librarians, content managers, taxonomists, archivists, and records managers to facilitate good communication among many types of stakeholders. We work to define how to apply behavioral business practices and tools to business problems. Understanding how a software product is helpful in processes, its potential applications, or to encourage usability standards are part of the knowledge manager’s toolkit. It is quite an art, the KM process of bringing tools together with knowledge assets (people and content) into a productive balance.

Search is one of the tools that can facilitate leveraging knowledge assets and help us find the experts who might share some “how-to” knowledge, but it is not, nor will it ever be a substitute for KM. You can check out these links to see how others line up on the definitions of KM: CIO introduction to KM and Wikipedia. Let’s not have the “KM is dead” discussion again!

When We Are Missing Good Metadata in Enterprise Search

This blog has not focused on non-profit institutions (e.g. museums, historical societies) as enterprises but they are repositories of an extraordinary wealth of information. The past few weeks I’ve been trying, with mixed results, to get a feel for the accessibility of this content through the public Web sites of these organizations. My queries leave me with a keen sense of why search on company intranets also fail.

Most sizable non-profits want their collections of content and other information assets exposed to the public. But each department manages its own content collections with software that is unique to their specific professional methods and practices. In the corporate world the mix will include human resources (HR), enterprise resource management (ERP) systems, customer relationship management (CRM), R & D document management systems and collaboration tools. Many corporations have or “had” library systems that reflected a mix of internally published reports and scholarly collections that support R & D and special areas such as competitive intelligence. Corporations struggle constantly with federating all this content in a single search system.

Non-profit organizations have similar disparate systems constructed for their special domain, museums or research institutions. One area that is similar between the corporate and non-profit sector is libraries, operating with software whose interfaces hearken back to designs of the late 1980s or 90s. Another by-product of that era was the catalog record in a format devised by the Library of Congress for the electronic exchange of records between library systems. It was never intended to be the format for retrieval. It is similar to the metadata in content management systems but is an order of magnitude more complex and arcane to the typical person doing searching. Only librarians and scholars really understand the most effective ways to search most library systems; therein lies the “public access” problem. In a corporation a librarian often does the searching.

However, a visitor to a museum Web site would expect to quickly find a topic for which the museum has exhibit materials, printed literature and other media, all together. This calls for nomenclature that is “public friendly” and reflects the basic “aboutness” of all the materials in museum departments and collections. It is a problem when each library and curatorial department uses a different method of categorizing. Libraries typically use Library of Congress Subject Headings. What makes this problematic is that topics are so numerous. The number of possible subject headings is designed for the entire population of all Library of Congress holdings, not a special collection of a few tens of thousands of materials. Almost no library systems search for words “contained in” the subject headings if you try to browse just the Subject index. If I am searching Subjects for all power generation materials and a heading such as electric power generation is used, it will not be found because the look-up mechanism only looks for headings that “begin with” power generation.

Let’s cut to the chase; mountains of metadata in the form of library cataloging are locked inside library systems within non-profit institutions. It is not being searched at the search box when you go to a museum Web site because it is not accessible to most “enterprise” or “web site” search engines. Therefore, a separate search must be done in the library system using a more complex approach to be truly thorough.

We have a big problem if we are to somehow elevate library collections to the same level of importance as the rest of a museum’s collections and integrate the two. Bigger still is the challenge of getting everything indexed with a normalized vocabulary for the comfort of all audiences. This is something that takes thought and coordination among professionals of diverse competencies. It will not be solved easily but it must be done for institutions to thrive and satisfy all their constituents. Here we have yet another example of where enterprise search will fail to satisfy, not because the search engine is broken but because the underlying data is inappropriately packaged for indexes to work as expected. Yet again, we come to the realization that we need people to recognize and fix the problem.

What Determines a Leader in the Enterprise Search Market?

Let’s agree that most if not all “enterprise search” is really about point solutions within large corporations. As I have written elsewhere, the “enterprise” is almost always a federation of constituencies, each with their own solutions for content applications and that includes search. If there is any place that we find truly enterprise-wide application of search, it is in small and medium organizations (SMBs). This would include professional service firms (consultancies and law firms), NGOs, many non-profits, and young R&D companies. There are plenty of niche solutions for SMBs and they are growing.

I bring this up because the latest Gartner “magic quadrant” lists Microsoft (MS) as the “leader” in enterprise search; this is the same place Gartner has positioned Fast Search & Transfer in the past. Whether this is because Fast’s assets are now owned by MS or because Gartner really believes that Microsoft is the leader, I still beg to strongly differ.

I have been perplexed by the Microsoft/Fast deal since it was announced earlier this year because, although Fast has always offered a lot of search technology, I never found it to be a compelling solutions for any of my clients. Putting aside the huge upfront capital cost for licenses, the staggering amount of development work, and time to deployment there were other concerns. I sensed a questionable commitment to an on-going, sustainable, unified and consistent product vision with supporting services. I felt that any client of mine would need very deep pockets indeed to really make a solid value case for Fast. Most of my clients are already burned out on really big enterprise deployments of applications in the ERP and CRM space, and understand the wisdom of beginning with smaller value-achievable, short-term projects on which they can build.

Products that impress me as having much more “out-of-the-box” at a more reasonable cost are clearly leaders in their unique domains. They have important clients achieving a good deal of benefit at a reasonable cost, in a short period of time. They have products that can be installed, implemented and maintained internally without a large staff of administrators, and they have good reputations among their clients for responsiveness and a cohesive series of roll-outs. Several have as many or more clients than Fast ever had (if we ever know the real number). Coveo, Exalead, ISYS, Recommind, Vivisimo, and X1 are a few of a select group that are marking a mark in their respective niches, as products ready for action with a short implementation cycle (weeks or months not years).

Autonomy and Endeca continue to bring value to very large projects in large companies but are not plug-and-play solutions, by any means. Oracle, IBM, and Microsoft offer search solutions of a very different type with a heavy vendor or third-party service requirement. Google Search Appliance has a much larger installed base than any of these but needs serious tuning and customization to make it suitable to enterprise needs. Take the “leadership” designation with a big grain of salt because what leads on the charts may be exactly what bogs you down. There are no generic, one-suit-fits-all enterprise search solutions including those in the “leaders” quadrant.

The Future of Enterprise Search

We’ve been especially focused on enterprise search this year. In addition to Lynda’s blog and our normal conference coverage, we have released two extensive reports, one authored by Lynda and one by Stephen Arnold, and Udi Manber VP Engineering, Search, Google, keynoted our San Francisco conference. We are continuing this focus at our upcoming Boston conference where Prabhakar Raghavan, Head of Yahoo! Research, will provide the opening keynote.

Prabhakar’s talk is titled “The Future of Search”. The reason I added “enterprise” to the title of the post, is that Prabhakar’s talk will be of special interest to enterprises because of its emphasis on complex data in databases and marked-up content repositories. Prabhakar’s background includes stints CTO at Verity and IBM so enterprise (or, if you prefer “behind-the-firewall”, or “intranet”) search requirements are not new to him.

Here is the description from the conference site:

Web content continues to grow, change, diversify, and fragment. Meanwhile, users are performing increasingly sophisticated and open-ended tasks online, connecting broadly to content and services across the Web. The simple search result page of blue text links needs to evolve to address these complex tasks, and this evolution includes a more formal understanding of user’s intent, and a deeper model of how particular pieces of Web content can help. Structured databases power a significant fraction of Web pages, and microformats and other forms of markup have been proposed as mechanisms to expose this structure. But uptake of these mechanisms remains limited, as content owners await the killer application for this technology. That application is search. If search engines can make deep use of structured information about content, provided through open standards, then search engines and site owners can together bring consumers a far richer experience. We are entering a period of massive change to enable search engines to handle more complex content. Prabhakar Raghavan, head of Yahoo! Research, will address the future of search: how search engines are becoming more sophisticated, what the breakthrough point will be for semantics on the Web and what this means for developers and publishers.

Join us on December 3rd at 8:30am at the Boston Westin Copley. Register.

Dewey Decimal Classification, Categorization, and NLP

I am surprised how often various content organizing mechanisms on the Web are compared to the Dewey Decimal System. As a former librarian, I am disheartened to be reminded how often students were lectured on the Dewey Decimal system, apparently to the exclusion of learning about subject categorization schemes. They complemented each other but that seems to be a secret among all but librarians.

I’ll try to share a clearer view of the model and explain why new systems of organizing content in enterprise search are quite different than the decimal model.

Classification is a good generic term for defining physical organizing systems. Unique animals and plants are distinguished by a single classification in the biological naming system. So too are books in a library. There are two principal classification systems for arranging books on the shelf in Western libraries: Dewey Decimal and Library of Congress (LC). They each use coding (numeric for Dewey decimal and alpha-numeric for Library of Congress) to establish where a book belongs logically on a shelf, relative to other books in the collection, according to the book’s most prominent content topic. A book on nutrition for better health might be given a classification number for some aspect of nutrition or one for a health topic, but a human being has to make a judgment which topic the book is most “about” because the book can only live in one section of the collection. It is probably worth mentioning that the Dewey and LC systems are both hierarchical but with different priorities. (e.g. Dewey puts broad topics like Religion and Philosophy and Psychology at top levels and LC puts those two topics together while including more scientific and technical topics at the top of the list, like Agriculture and Military Science.)

So why classify books to reside in topic order? It requires a lot of labor to move the collections around to make space for new books. It is for the benefit of the users, to enable “browsing” through the collection, although it may be hard to accept that the term browsing was a staple of library science decades before the internet. Library leaders established eons ago the need for a system of physical organization to help readers peruse the book collection by topic, leading from the general to the specific.

You might ask what kind of help that was for finding the book on nutrition that was classified under “health science.” This is where another system, largely hidden from the public or often made annoyingly inaccessible, comes in. It is a system of categorization in which any content, book or otherwise, can be assigned an unlimited number of categories. Wondering through the stacks, one would never suspect this secret way of finding a nugget in a book about your favorite hobby if that book was classified to live elsewhere. The standard lists of terms for further describing books by multiple headings are called “subject headings” and you had to use a library catalog to find them. Unfortunately, they contain mysterious conventions called “sub-divisions,” designed to pre-coordinate any topic with other generic topics (e.g. Handbooks, etc. and United States). Today we would call these generic subdivision terms, facets. One reflects a kind of book and the other reveals a geographical scope covered by the book.

With the marvel of the Web page, hyperlinking, and “clicking through” hierarchical lists of topics we can click a mouse to narrow a search for handbooks on nutrition in the United States for better health beginning at any facet or topic and still come up with the book that meets all four criteria. We no longer have to be constrained by the Dewey model of browsing the physical location of our favorite topics, probably missing a lot of good stuff. But then we never did. The subject card catalog gave us a tool for finding more than we would by classification code alone. But even that was a lot more tedious than navigating easily through a hierarchy of subject headings, narrowing the results by facets on a browser tab and further narrowing the results by yet another topical term until we find just the right piece of content.

Taking the next leap we have natural language processing (NLP) that will answer the question, “Where do I find handbooks on nutrition in the United States for better health?” And that is the Holy Grail for search technology – and a long way from Mr. Dewey’s idea for browsing the collection.

MicroLink Launches MicroLink Autonomy Integration Suite for SharePoint

MicroLink announced the release of MicroLink Autonomy Integration Suite (AIS) for SharePoint 2003/2007, which consists of six web parts that integrate Autonomy’s Data Operating Layer (IDOL) server with Microsoft Office SharePoint Server (MOSS). This integration allows SharePoint users to leverage Autonomy’s information discovery capability and automated features in a unified platform. MicroLink’s Autonomy Integration Suite for SharePoint consists of custom web parts that create more efficient access to the search capabilities of Autonomy’s IDOL server from within SharePoint. With interfaces familiar to SharePoint users, AIS helps organizations to process digital content automatically, share data and synchronize with other data webparts. AIS comprises Search and Retrieval, Agents, Profiling, Web Channels, Clustering, and Community Collaboration. AIS also improves expertise search and incorporates full document level security. Key Features of AIS: Federated search capabilities for SharePoint, enabling customers to index and search all content across the entire enterprise and repositories inside and outside the SharePoint environment; Custom Web Parts that enable access to the capabilities of Autonomy’s IDOL platform from within Microsoft’s SharePoint Portal Server; Data connections for each web part that allows data sharing and synchronization between parts; For the end user, a singular interface that is consistent with the SharePoint user experience. http://www.MicroLinkllc.com

Controlling Your Enterprise Search Application

When interviewing search administrators who had also been part of product selection earlier this year, I asked about surprises they had encountered. Some involved the selection process but most related to on-going maintenance and support. None commented on actual failures to retrieve content appropriately. That is a good thing whether it was because, during due diligence they had already tested for that during a proof of concept or because they were lucky.

Thinking about how product selections are made, prompts me to comment on a two major search product attributes that control the success or failure of search for an enterprise. One is the actual algorithms that control content indexing, what is indexed and how it is retrieved from the index (or indices). The second is the interfaces, interfaces for the population of searchers to execute selections, and interfaces for results presentation. On each aspect, buyers need to know what they can control and how best to execute it for success.

Indexing and retrieval technology is embedded with search products; the number of administrative options to alter search scalability, indexing and content selection during retrieval is limited to none. The “secret sauce” for each product is largely hidden, although it may have patented aspects available for researching. Until an administrator of a system gets deeply into tuning, and experimenting with significant corpuses of content, it is difficult to assess the net effect of delivered tuning options. The time to make informed evaluations about how well a given product will retrieve your content when searched by your select audience is before a purchase is made. You can’t control the underlying technology but you can perform a proof of concept (PoC). This requires:

  • human resources and a commitment of computing resources
  • well-defined amount, type and nature (metadata plus full-text or full-text unstructured-only) to give a testable sample
  • testers who are representative of all potential searchers
  • a comparison of the results with three to four systems to reveal how well they each retrieve the intended content targets
  • knowledge of the content by testers and similarity of searches to what will be routinely sought by enterprise employees or customers
  • search logs of previously deployed search systems, if they exist. Searches that routinely failed in the past should be used to test newer systems

Interface technology
Unlike the embedded search technology, buyers can exercise design control or hire a third-party to produce search interfaces that vary enormously. Controlling for what searchers experience when they first encounter a search engine, either a search box at a portal or a completely novel variety of search options with search box, navigation options or special search forms is within the control of the enterprise. This may be required if what comes “out-of-the box” as the default is not satisfactory. You may find, at a reasonable price, a terrific search engine that scales well, indexes metadata and full-text competently and retrieves what the audience expects but requires a different look-and-feel for your users. Through an API (application programming interface), SDK (software development kit) or application connectors (e.g. Documentum, SharePoint) numerous customization options are delivered with enterprise search packages or are available as add-ons.

In either case, human resource costs must be added to the bottom line. A large number of mature software companies and start-ups are innovating with both their indexing techniques and interface design technologies. They are benefiting from several decades of search evolution for search experts, and now a decade of search experiences in the general population. Search product evolution is accelerating as knowledge of searcher experiences is leveraged by developers. You may not be able to control emerging and potentially disruptive technologies, but you can still exercise beneficial controls when selecting and implementing most any search system.

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