The XML Query Working Group has published the Candidate Recommendation of “XQuery Update Facility 1.0.” This document defines an update facility that extends the “XML Query language, XQuery.” The XQuery Update Facility provides expressions that can be used to make persistent changes (including node insertion, deletion, modification, and creation) to instances of the XQuery 1.0 and XPath 2.0 Data Model. The Working Group also published two additional documents that will become Working Group notes– ” XQuery Update Facility 1.0 Requirements” and “XQuery Update Facility 1.0 Use Cases.” http://www.w3.org/XML/Query/
Category: Semantic technologies (Page 33 of 72)
Our coverage of semantic technologies goes back to the early 90s when search engines focused on searching structured data in databases were looking to provide support for searching unstructured or semi-structured data. This early Gilbane Report, Document Query Languages – Why is it so Hard to Ask a Simple Question?, analyses the challenge back then.
Semantic technology is a broad topic that includes all natural language processing, as well as the semantic web, linked data processing, and knowledge graphs.
SYSTRAN announced the release of SYSTRAN Enterprise Server 6, a solution that meets the full range of enterprise language translation needs. Enterprise Server 6 enables corporate users to understand multilingual information in real-time and to deliver consistent and validated translations enabling them to follow best business practices and communicate across different languages. Available in three editions targeted to the small and midsized businesses and enterprise platforms, Enterprise Server 6 addresses complex translation tasks and provides a workbench for managing translation projects. The solution automatically translates all types of documents and files ranging from manuals, procedures, reports, product and support information, content applications, websites, and all written texts. It translates most file types through a Web-based interface or a SYSTRAN Toolbar available on the user desktop. Corporations can integrate it into enterprise applications to drive multilingual information in and across channels, like the enterprise content management system, portal, search, website, etc. Common uses include adding an online translation service to the corporate intranet, on-demand website translation, localization for document workflows, integration with content management systems, databases, and other enterprise applications. SYSTRAN Enterprise Server 6, Workgroup Edition is designed for the small enterprise Intranet with up to 100 users. Price starts at $15,000. SYSTRAN Enterprise Server 6, Standard Edition is designed for the midsize Intranet or Extranet with up to 2,500 users using the Online Tools and Application Packs. Price starts at $30,000. SYSTRAN Enterprise Server 6, Global Edition is designed for enterprises with advanced translation requirements with unlimited user access. Price starts at $150,000. http://www.systransoft.com/
X1 Technologies, Inc., released a new enterprise search suite for Symantec Enterprise Vault. X1 Search Suite for Symantec Enterprise Vault provides an intuitive graphical interface to find, preview and act upon documents, email and attachments regardless of location. The X1 Search Suite for Symantec Enterprise Vault enhances customer productivity by providing the ability to search both the contents of the Vault and data residing in email applications and files. The X1 Search Suite for Symantec Enterprise Vault consists of three components. The first two consist of the scalable X1 Enterprise Server combined with the X1 Content Connector for Symantec Enterprise Vault that provide true search federation and do not duplicate data. By using native API connectivity, the security of the user’s company security model is preserved and does not facilitate retention policy violations. Lastly, the X1 Suite includes the X1 Enterprise Search Client which provides a single search interface where users can search multiple vaults along with data in 3rd party email packages and in over 400 file formats. Users can then use the X1 client to preview and act upon the search results; including native Symantec Enterprise Vault actions. http://www.x1.com
Recent studies describe the negative effect of media including video, television and on-line content on attention spans and even comprehension. One such study suggests that the piling on of content accrued from multiple sources throughout our work and leisure hours has saturated us to the point of making us information filterers more than information “comprehenders”. Hold that thought while I present a second one.
Last week’s blog entry reflected on intellectual property (IP) and knowledge assets and the value of taxonomies as aids to organizing and finding these valued resources. The idea of making search engines better or more precise in finding relevant content is edging into our enterprises through semantic technologies. These are search tools that are better at finding concepts, synonymous terms, and similar or related topics when we execute a search. You’ll find an in depth discussion of some of these in the forthcoming publication, Beyond Search by Steve Arnold. However, semantic search requires more sophisticated concept maps than taxonomy. It requires ontology, rich representations of a web of concepts complete with all types of term relationships.
My first comment about a trend toward just browsing and filtering content for relevance to our work, and the second one about the idea of assembling semantically relevant content for better search precision are two sides of a business problem that hundreds of entrepreneurs are grappling with, semantic technologies.
Two weeks ago, I helped to moderate a meeting on the subject, entitled Semantic Web – Ripe for Commercialization? While the assumed audience was to be a broad business group of VCs, financiers, legal and business management professionals, it turned out to have a lot of technology types. They had some pretty heavy questions and comments about how search engines handle inference and its methods for extracting meaning from content. Semantic search engines need to understand both the query and the target content to retrieve contextually relevant content.
Keynote speakers and some of the panelists introduced the concept of ontologies as being an essential backbone to semantic search. From that came a lot of discussion about how and where these ontologies originate, how and who vets them for authoritativeness, and how their development in under-funded subject areas will occur. There were no clear answers.
Here I want to give a quick definition for ontology. It is a concept map of terminology which, when richly populated, reflects all the possible semantic relationships that might be inferred from different ways that terms are assembled in human language. A subject specific ontology is more easily understood in a graphical representation. Ontologies also help to inform semantic search engines by contributing to an automated deconstruction of a query (making sense out of what the searcher wants to know) and automated deconstruction of the content to be indexed and searched. Good semantic search, therefore, depends on excellent ontologies.
To see a very simple example of an ontology related to “roadway”, check out this image. Keep in mind that before you aspire to implementing a semantic search engine in your enterprise, you want to be sure that there is a trusted ontology somewhere in the mix of tools to help the search engine retrieve results relevant to your unique audience.
Attensity announced Attensity VoC On-Demand, a new secure software as a service (SaaS) that enables users to access the company’s “Voice of the Customer” (VoC) solution via the Web for on-demand customer feedback analysis. Enterprises can now extract and analyze data about their customers in Attensity’s user interface and through customizable analytic dashboards. Attensity’s VoC solution uses the company’s Exhaustive Extraction engine to automatically identify facts, opinions, requests, trends and trouble areas from unstructured first person feedback found in surveys, service and call center notes, emails, web forums, blogs, news articles and other forms of customer contact. Attensity turns the first person feedback into “First Person Intelligence”, enabling Attensity users to proactively understand and rapidly react to customer issues and requests. They also have the ability to discover product and/or service offering opportunities as well as potential areas for improvement. Attensity VoC On-Demand also offers a quick start implementation program, which includes appropriate data preparation – dictionary, domain and categorization development – to prepare data sets for extraction and output views and dashboards. Users can develop predefined analysis views, known as query templates, and dashboards tailored to the user organization’s requirements. http://www.attensity.com
We’ll be publishing our special report by Stephen Arnold, Beyond Search: What to do When you’re Enterprise Search System Doesn’t Work soon – most likely at the beginning of April, and have set-up a page where you can sign-up to be notified when the report will be available at . There will also be a special price for early orders and we’ll be providing that info shortly.
Steve has also set-up a page describing the report at: , and has a blog where he is providing some supplementary material. Also keep an eye on Lynda’s blog where she might have some comments while she is doing some editing.
This blog entry on the “Taxonomy Watch” website prompts me to correct the impression that I believe naysayers who say that taxonomies take too much time and effort to be valuable. Nothing could be further from the truth. I believe in and have always been highly vested in taxonomies because I am convinced that an investment in pre-processing enterprise generated content into meaningfully organized results brings large returns in time savings for a searcher. S/he, otherwise, needs to invest personally in the laborious post-processing activity of sifting and rejecting piles of non-relevant content. Consider that categorizing content well and only once brings benefit repeatedly to all who search an enterprise corpus.
Prime assets of enterprises are people and their knowledge; the resulting captured information can be leveraged as knowledge assets (KA). However, there is a serious problem “herding” KA into a form that results in leveragable knowledge. Bringing content into a focus that is meaningful to a diverse but specialized audience of users, even within a limited company domain is tough because the language of the content is so messy.
So, what does this have to do with taxonomies and enterprise search, and how they factor into leveraging KA? Taxonomies have a role as a device to promote and secure the meaningful retrievability of content when we need it most or fastest, just-in-time retrieval. If no taxonomies exist to pre-collocate and contextualize content for an audience, we will be perpetually stuck in a mode of having to do individual human filtering of excessive search results that come from “keyword” queries. If we don’t begin with taxonomies for helping search engines categorize content, we will certainly never get to the holy grail of semantic search. We need every device we can create and sustain to make information more findable and understandable; we just don’t have time to both filter and read, comprehensively, everything a keyword search throws our way to gain the knowledge we need to do our jobs.
Experts recognize that organizing content with pre-defined terminology (aka controlled vocabularies) that can be easily displayed in an expandable taxonomic structure is a useful aid for a certain type of searcher. The audience for navigated search is one that appreciates the clustering of search results into groups that are easily understood. They find value in being able to move easily from broad concepts to narrower ones. They especially like it when the categories and terminology are a close match to the way they view a domain of content in which they are subject experts. It shows respect for their subject area and gives them a level of trust that those maintaining the repository know what they need.
Taxonomies, when properly employed, serve triple duty. Exposing them to search engines that are capable of categorizing content puts them into play as training data. Setting them up within content management systems provides a control mechanism and validation table for human assigned metadata. Finally, when used in a navigated search environment, they provide a visual map of the content landscape.
U.S. businesses are woefully behind in “getting it;” they need to invest in search and surrounding infrastructure that supports search. Comments from a recent meeting I attended reflected the belief that the rest of the world is far ahead in this respect. As if to highlight this fact, a colleague just forwarded this news item yesterday. “On February 13, 2008, the XBRL-based financial listed company taxonomy formulated by the Shanghai Stock Exchange (SSE) was “Acknowledged” by the XBRL International. The acknowledgment information has been released on the official website of the XBRL International (http://www.xbrl.org/FRTaxonomies/)….”.
So, let’s get on with selling the basic business case for taxonomies in the enterprise to insure that the best of our knowledge assets will be truly findable when we need them.
This week’s thoughts come from the pile of serendipitous reading that routinely piles up on my desk. In this case a short article in Information Week caught my eye because it featured the husband of a former neighbor, Ken Krugler, co-founder of Krugle. I’d set it aside because a fellow, David Eddy, in my knowledge management forum group keeps telling us that we need tools to facilitate searching for old but still useful source code. In order to do it, he believes, we need an investment in semantic search tools that normalize the voluminous language variants scattered throughout source code. That would enable programmers to find code that could be re-purposed in new applications.
Now, I have taken the position that source code is just one set of intellectual property (IP) asset that is wasted, abandoned and warehoused for technology archaeologists of centuries hence. I just don’t see a solid business case being made to develop search tools that will become a semantic search engine for proprietary treasure troves of code.
Enters old acquaintance Ken Krugler with what seems to be, at first glance, a Web search system that might be helpful for finding useful code out on the Web, including open source. I have finally visited his Web site and I see language and new offerings that intrigue me. “Krugle Enterprise is a valuable tool for anyone involved in software development. Krugle makes software development assets easily accessible and increases the value of a company’s code base. By providing a normalized view into these assets, wherever they may be stored, Krugle delivers value to stakeholders throughout the enterprise.” They could be onto something big. This is a kind of enterprise search I haven’t really had time to think about but may-be I will now.
One thing leading to another, I checked out Ken Krugler’s blog and saw an earlier posting: Is Writing Your Own Search Engine Hard? This is recommended reading for anyone who even dabbles in enterprise search technology but doesn’t want to get her/his hands dirty with the mechanics. It is short, to-the-point and summarizes how and why so many variations of search are battling it out in the marketplace.
I don’t want end-users to struggle too much with the under the hood details but when you are thinking about enterprise search for your organization, it is worth considering how much technology you are getting for the value you want it to deliver, year after year, as your mountains of IP content accrue. Don’t give this idea short shrift because search is an investment that keeps giving if it is chosen appropriately for the problem you need to solve.
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