April 20, 2015
Expert System offers a system capable of turbo-charging information access in SharePoint installations. The company has developed a fact-based webinar to demonstrate the power of Expert System’s semantic technology.
The company’s Cogito Connected for SharePoint features a document library, complete with metadata enrichment for files to increase their visibility as well as their content. The library will also be retained in SharePoint and be available for use by other files and accurate time and date of most recent tagging will be captured for each file. Users will also be able to process multiple attachments in the Document List and the search function is enhanced with fully integrated Web components.
With Cogito, users can locate content via a custom taxonomy, entities, or faceted search options. SharePoint users can locate needed information via point-and-click, eDiscovery, and traditional keyword search enriched with organization-specific metadata. Expert System’s Cogito allows users to browse content organized by topics, people, and concepts, which makes SharePoint more useful to a busy professional.
SharePoint is one of the most popular collaborative content platforms for enterprise systems, but like many proprietary software programs it has its limits. The good news is that companies like Expert System discover SharePoint’s weaknesses and create solutions to fix them.
Using its patented technology Cogito, Expert System addresses one of the main user concerns when looking for information housed in SharePoint. Cogito sharply reduces the difficulty of navigating and locating content in SharePoint. This problem stems from creators improperly tagging content or not tagging it at all.
“Cogito Connected for SharePoint addresses these two areas by providing the power of Cogito semantics to the application of consistent, automated tagging of SharePoint content. With the addition of fully integrated web parts that expose the granularity of content generated metadata, Cogito enhanced SharePoint optimizes the management of content for the SharePoint administrator. For the user, Cogito Connected for SharePoint significantly improves the SharePoint search experience by enhancing the search capabilities beyond the list to include faceted search including category, entity and topic.”
Expert System’s solution delivers a better SharePoint experience for the user and improves work productivity for employees, since they will be able to locate information quicker. Expert System knows what many users don’t realize: the value of being able to locate and recognize content quickly. In this case, Expert System applied this knowledge to SharePoint, but it can be used for other programs in any field. On April 28, 2015 from 12:00 PM-1:00 PM EST, Expert System will host a free webinar called “Implementing a Better Search Experience” where attendees will “learn how to make SharePoint more than a place where you put documents and start transforming your collected knowledge in your collective knowledge.”
Expert System was founded in 1989 and its flagship product is Cogito. Solutions based on the Cogito software include semantic search, natural language search, text analytics, development and management of taxonomies and ontologies, automatic categorization, extraction of data and metadata, and natural language processing. Expert System is working on exciting new developments on everything from enterprise systems to security and intelligence.
Expert System wants to share its knowledge with users so they can have a better user experience, apply the knowledge to other areas, and, of course, make daily tasks simpler.
The new “Implementing a Better Search Experience” will be offered on April 28, 2015, from 12 to 1 pm Eastern Time. You will learn how you can transform your organization’s collected knowledge in actionable collective knowledge.
Sign up for the April webinar at http://bit.ly/1FalGjH.
Stephen E Arnold, April 20, 2015
April 15, 2015
I have a view of Yahoo. Sure, it was formed when I was part of the team that developed The Point (Top 5% of the Internet). Yahoo had a directory. We had a content processing system. We spoke with Yahoo’s David Filo. Yahoo had a vision, he said. We said, No problem.
The Point became part of Lycos, embracing Fuzzy and his round ball chair. Yahoo, well, Yahoo just got bigger and generally went the way of general purpose portals. CEOs came and went. Stakeholders howled and then sulked.
I read or rather looked at “Yahoo. Semantic Search From Document Retrieval to Virtual Assistants.” You can find the PowerPoint “essay” or “revisionist report” on SlideShare. The deck was assembled by the director of research at Yahoo Labs. I don’t think this outfit is into balloons, self driving automobiles, and dealing with complainers at the European Commission. Here’s the link. Keep in mind you may have to sign up with the LinkedIn service in order to do anything nifty with the content.
The premise of the slide deck is that Yahoo is into semantic search. After some stumbles, semantic search started to become a big deal with Google and rich snippets, Bing and its tiles, and Facebook with its Like button and the magical Open Graph Protocol. The OGP has some fascinating uses. My book CyberOSINT can illuminate some of these uses.
And where is Yahoo in the 2008 to 2010 interval when semantic search was abloom? Patience, grasshopper.
Yahoo was chugging along with its Knowledge Graph. If this does not ring a bell, here’s the illustration used in the deck:
The date is 2013, so Yahoo has been busy since Facebook, Google, and Microsoft were semanticizing their worlds. Yahoo has a process in place. Again from the slide deck:
I was reminded of the diagrams created by other search vendors. These particular diagrams echo the descriptions of the now defunct Siderean Software server’s set up. But most content processing systems are more alike than different.
April 6, 2015
We have hear a lot about the semantic Web and search engine optimization (SEO), but both have the common thread of making information more accessible and increasing its use. One would think this would be the same kettle of fish, but sometimes it is hard to make SEO and the semantic Web work together for platonic web experience. On Slideshare.net, Eric Franzon’s “SEO Meets Semantic Web-Saint Patrick’s Day 2015-Meetup” tries to consolidate the two into one happy fish taco. The presentation tries to explain how the two work together, but here is the official description:
“Schema.org didn’t just appear out of thin air in 2011. It was built upon a foundation of web standards and technologies that have been in development for decades. In this presentation, Eric Franzon, Managing Partner of SemanticFuse provides an introduction to Semantic Web standards such as RDF and SPARQL. He explores who’s using them today and why (hint: it involves money), and takes a look at how Semantic Web, Linked Data, and schema.org are related.”
The problem with the presentation is that we do not have the audio to accompany it, but by flipping through the slides we can understand the general idea. The semantic Web is full of relationships that are connected by ideas and require coding and other fancy stuff to make it one big kettle. In fact, this appears to have too much of the semantic Web flavor and not enough of the SEO spice. One is a catfish for fine meal and the other is a fish fry without the oil.
Whitney Grace, April 6, 2015
Stephen E Arnold, Publisher of CyberOSINT at www.xenky.com
April 4, 2015
March 28, 2015
I read “Goodbye Blekko: Search Engine Joins IBM’s Watson Team.” According to the write up, “Blekko’s home page says its team and technology are now part of IBM’s Watson technology.” I would not know this. I do not use the service. I wrestled with the implementation of Blekko on a news service and then wondered if Yandex was serious about the company. Bottom line: Blekko is not one of my go to search systems, and I don’t cover it in my Alternatives to Google lectures for law enforcement and intelligence professionals.
The write up asserts:
Blekko came out of stealth in 2008 with Skrenta promising to create a search engine with “algorithmic editorial differentiation” compared to Google. Its public search engine finally opened in 2010, launching with what the site called “slashtags” — a personalization and filtering tool that gave users control over the sites they saw in Blekko’s search results.
Another search system becomes part of the puzzling Watson service. How many information access systems does IBM require to make Watson the billion dollar revenue generator or at least robust enough to pay the rent for the Union Square offices?
IBM “owns” the Clementine system which arrived with the SPSS purchase. IBM owns Vivisimo, which morphed into a Big Data system in the acquisition news release, iPhrase, and the wonky search functions in DB2. Somewhere along the line, IBM snagged the Illustra system. From its own labs, IBM has Web Fountain. There is the decades old STAIRS system which may still be available as Service Master. And, of course, there is the Lucene system which provides the dray animals for Watson. Whew. That is a wealth of information access technology, and I am not sure it is comprehensive.
My point is that Blekko and its razzle dazzle assertions now have to provide something that delivers a payoff for IBM. On the other hand, maybe IBM Watson executives are buying technology in the hopes that one of the people “aquihired” or the newly bought zeros and ones will generate massive cash flows.
Watson has morphed from a question answering game show winner into all manner of fantastic information processing capabilities. For me, Watson is an example of what happens when a lack of focus blends with money, executive compensation schemes, and a struggling $100 billion outfit.
Lots of smoke. Not much revenue fire. Stakeholders hope it will change. I am looking forward to a semantically enriched recipe for barbeque sauce that includes tamarind and other spices not available in Harrod’s Creek, Kentucky. Yummy. A tasty addition to the quarterly review menu: Blekko with revenue and a piquant profit sauce.
Perhaps IBM next will acquire Pertimm and the Qwant search system which terrrifes Eric Schmidt? Surprises ahead. I prefer profitable, sustainable revenues however.
Stephen E Arnold, March 28, 2015
March 27, 2015
I read “The Rapid Evolution of Semantic Search.” It must be my age or the fact that it is cold in Harrod’s Creek, Kentucky, this morning. The write up purports to deliver “an overview of the history of semantic search and what this means for marketers moving forward.” I like that moving forward stuff. It reminds me of Project Runway’s “fashion forward.”
The write up includes a wonky graphic that equates via an arrow Big Data and metadata, volume, smart content, petabytes, data analysis, vast, structured, and framework. Big Data is a cloud with five little arrows pointing down. Does this mean Big Data is pouring from the sky like yesterday’s chilling rain?
The history of the Semantic Web begins in 1998. Let’s see that is 17 years ago. The milestone is in the context of the article, the report “Semantic Web road Map.” I learned that Google was less than a month old. I thought that Google was Backrub and the work on what was named Google begin a couple, maybe three years, earlier. Who cares?
The Big Idea is that the Web is an information space. That sounds good.
Well in 2012, something Big happened. According to the write up Google figured out that 20 percent of its searches were “new.” Aren’t those pesky humans annoying. The article reports:
long tail keywords made up approximately 70 percent of all searches. What this told Google was that users were becoming interested in using their search engine as a tool for answering questions and solving problems, not just looking up facts and finding individual websites. Instead of typing “Los Angeles weather,” people started searching “Los Angeles hourly weather for March 1.” While that’s an extremely simplified explanation, the fact is that Google, Bing, Facebook, and other internet leaders have been working on what Colin Jeavons calls “the silent semantic revolution” for years now. Bing launched Satori, a knowledge storehouse that’s capable of understanding complex relationships between people, things, and entities. Facebook built Knowledge Graph, which reveals additional information about things you search, based on Google’s complex semantic algorithm called Hummingbird.
Yep, a new age dawned. The message in the article is that marketers have a great new opportunity to push their message in front of users. In my book, this is one reason why running a query on any of the ad supported Web search engines returns so much irrelevant information. In my just submitted Information Today column, I report how a query for the phrase “concept searching” returned results littered with a vendor’s marketing hoo-hah.
I did not want information about a vendor. I wanted information about a concept. But, alas, Google knows what I want. I don’t know what I want in the brave new world of search. The article ignores the lack of relevance in results, the dust binning of precision and recall, and the bogus information many search queries generate. Try to find current information about Dark Web onion sites and let me know how helpful the search systems are. In fact, name the top TOR search engines. See how far you get with Bing, Google, and Yandex. (DuckDuckGo and Ixquick seem to be aware of TOS content by the way.)
So semantic in the context of this article boils down to four points:
- Think like an end user. I suppose one should not try to locate an explanation of “concept searching.” I guess Google knows I care about a company with a quite narrow set of technology focused on SharePoint.
- Invest in semantic markup. Okay, that will make sense to the content marketers. What if the system used to generate the content does not support the nifty features of the Semantic Web. OWL, who? RDF what?
- Do social. Okay, that’s useful. Facebook and Twitter are the go to systems for marketing products I assume. Who on Facebook cares about cyber OSINT or GE’s cratering petrochemical business?
- And the keeper, “Don’t forget about standard techniques.” This means search engine optimization. That SEO stuff is designed to make relevance irrelevant. Great idea.
Net net: The write up underscores some of the issues associated with generating buzz for a small business like the ones INC Magazine tries to serve. With write ups like this one about Semantic Search, INC may be confusing their core constituency. Can confused executives close deals and make sense of INC articles? I assume so. I know I cannot.
Stephen E Arnold, March 27, 2015
March 3, 2015
The article on the blog Realizing Semantic Web titled Semantic Web – Story So Far explores where exactly credit it due for the current state of Semantic Web technology. The author notes that as of 2004, there were very few tools for developers interested in investing time and money. Between then and 2010, quite a leap forward took place, with major improvements in the standards and practices of the Semantic Web technology. The article aims to acknowledge the people and companies that did the most important work. The list includes,
“Tim Berners Lee for believing when we all thought Semantic web might not work and will be another AI failure. And of course for his His work at the W3C. James Handler – in addition to his continued work on Semantic Web, for coming up with gems such as the definition of Semantics/Linked Data Cloud that is most effective….DBPedia & Linked Data Cloud…OWL/RDF/SKOS…Google Refine and similar efforts…BBC & other case studies…”
This list does, however, still seem incomplete and somewhat partial. The author even suggests that more input might be needed, but he only allows for two or so more additions. Is this an accurate reflection of the development of the Semantic Web?
Chelsea Kerwin, March 03, 2015
January 7, 2015
Social search was supposed to integrate social media and regular semantic search to create a seamless flow of information. This was one of the major search points for a while, yet it has not come to fruition. So what happened? TechCrunch reports that it is “Good Riddance To Social Search” and with good reason, because the combination only cluttered up search results.
TechCrunch explains that Google tried Social Search back in 2009, using its regular search engine and Google+. Now the search engine mogul is not putting forth much effort in promoting social search. Bing tried something by adding more social media features, but it is not present in most of its search results today.
Why did this endeavor fail?
“I think one of the reasons social search failed is because our social media “friendships” don’t actually represent our real-life tastes all that well. Just because we follow people on Twitter or are friends with old high school classmates on Facebook doesn’t mean we like the same restaurants they do or share the politics they do. At the end of the day, I’m more likely to trust an overall score on Yelp, for example, than a single person’s recommendation.”
It makes sense considering how many people consider their social media feeds are filled with too much noise. Having search results free of the noiwy makes them more accurate and helpful to users.
December 31, 2014
An article published on Innography called “Advanced Patent Search” brings to attention how default search software might miss important search results, especially if one is researching patents. It points pout that some parents are purposefully phrased to cause hide their meaning and relevance to escape under the radar.
Deeper into the article it transforms into a press release highlight Innography’s semantic patent search. It highlights how the software searches through descriptive task over product description, keywords, and patent abstracts. This is not anything too exciting, but this makes the software more innovative:
“Innography provides fast and comprehensive metadata analysis as another method to find related patents. For example, there are several “one-click” analyses from a selected patent – classification analysis, citation mining, invalidation, and infringement – with a user-selected similarity threshold to refine the analyses as desired. The most powerful and complete analyses utilize all three methods – keyword search, semantic search, and metadata analysis – to ensure finding the most relevant patents and intellectual property to analyze further.”
Innography’s patent search serves as an example for how search software needs to compete with comparable products. A simple search is not enough anymore, not in the world of big data. Users demand analytics, insights, infographics, easy of use, and accurate results.
December 31, 2014
IT developers are searching for new ways to manipulate semantic search, but according to Search Engine Journal in “12 Things You Need To Do For Semantic Search” they are all trying to figure out what the user wants. The article offers twelve tips to get back to basics and use semantic search as a tool to drive user adoption.
Some of the tips are quite obvious, such as think like a user, optimize SEO, and harness social media and local resources. Making a Web site stand out, requires taking the obvious tips and using a bit more. The article recommends that it is time to learn more about Google Knowledge Graph and how it applies to your industry. Schema markup is also important, because search engines rely on it for richer results and it develops how users see your site in a search engine.
Here is some advice on future proofing you site:
“Work out how your site can answer questions and provide users with information that doesn’t just read like terms and conditions. Pick the topics, services and niches that apply to your site and start to optimize your site and your content in a way that will benefit users. Users will never stop searching using specific questions, but search engines are actively encouraging them to ask a question or solve a problem so get your services out there by meeting user needs.”
More tips include seeing how results are viewed on search engines other than Google, keeping up with trends, befriending a thesaurus, and being aware that semantic search requires A LOT of work.