Hakia Helps Pick Stock Winners
January 13, 2011
SENSEnews.com by Hakia uses advanced semantic algorithms to analyze news and social media coverage to determine which stocks are over or under valued. In this way, they can offer a “best-stock-picks” portfolio for the market.
Does it work? Here’s what we noted:
Over a 6-month period, the SENSEnews stock indicator has consistently produced higher returns than that of the DJIA and S&P 500 indices.
If this sounds tempting, it’s currently available to a limited number of participants for a monthly subscription and will be available to enterprises later this year.
Alice Wasielewski, January 11, 2011
2007 Semantic Search Info Still Relevant
January 13, 2011
Short honk. We had a long call today (January 12, 2011) about semantic search. In the course of the call, I mentioned a presentation by Jon Atle Gulla, a profession in 2007 at the Norwegian University of Science and Technology. I did some poking around and found the link to the presentation. Quite useful in 2007 and still germane today. The presentation puts into context some of the work that must be done to deploy an effective semantic technology system in an organization. The slide deck is on Slideshare at this link. Registration may be required to access the file.
Stephen E Arnold, January 13, 2011
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Semantics: Hot Again?
January 11, 2011
We hear this each year: Semantics will be hot in [fill in the year].
Kazeon’s The Future eDiscovery Arms Race: It is all about the Semantics investigates where the eDiscovery market must go in order to handle the growing volume of ESI while progressing the efficiency, accuracy and reliability of the search result process. After posing this question, where does Kazeon end up? At the doorstep of Semantics Future Institute.
Those who only speak English may not realize what a complicated language we really have. Words used regularly often carry several meanings, at times even four or more definitions to a single word. This is known as polysemy, and it throws a huge wrench in the search method.
We are beginning to see some workarounds to this issue finally realized. One of the major players is Latent Semantic Analysis, which plainly “searches documents for themes within the language usage and extracts the concepts, which are common to the documents”, helping to alleviate false positive results. Other aides include Word Search Disambiguation, which focuses on word meaning rather than merely matching character strings and Local Co-Occurrence Statistics, which counts how often sets of terms appear together within a predetermined period.
These tools will no doubt be helpful in refining search techniques, but our main question is, where was Kazeon five years ago when the semantic buzz began?
Sarah Rogers, January 11, 2011
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Any.Do for Voice to Device Actions Technology
January 10, 2011
When I was running around Central America a week ago, I received from one of my two or three readers a link to a story in VC Cafe with the title “Stealthy Startup Any.do Raises $1 Million Seed Round for Voice Mobile Commands. There is precious little information about the company available, but the article mentioned two individuals who have pumped some dough into the outfit. One is Google’s Eric Schmidt and the other is Joe Londsdale, a founder of Palantir. There are some other smart money investors, but I find the Schmidt and Londsdale references most interesting.
What’s Any.do do?
Based on what information I have, one talks to a mobile device and the Any.Do technology figures out what one says. With this information, Any.Do makes the instructions happen. Here’s VC Cafe’s summary:
[Any.Do is] developing technology to translate the user’s natural language voice input to the mobile device into actions, using voice recognition and semantic analysis algorithms…. AnyDo is capable of understanding subtle differences, such as the ability to purchase a product offline vs. online, pay bills on the mobile, purchase insurance, etc, using voice commands on the mobile.
The company’s Web site says, “Any.Do helps you do more of the things you love doing.” You can sign up to get information about the company at http://any.do.
I learned that Any.Do has developed an application for Android. Any.Do seems poised to release a product something this year. If it gets magnetic, maybe the Google will buy the company. I heard that at least one Googler works at the company now.
Stephen E Arnold, January 10, 2011
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Semantic Web Fire Starting from Google
January 5, 2011
“Welcome to Metaweb” on YouTube showcases the startup Metaweb Technologies, home of Freebase, acquired by Google in July 2010. The cute video belies the huge difficulty of what librarians refer to as authority control, but in this case organizing concepts for the entire web. An admirable project, for sure, but I wonder how much effort The Math Club is really planning to put into this idea. After all, Google has a history of both not doing much with the startups it takes over, and also of figuring out semantic relationships rather than having them created. Maybe this purchase is simply a way of acquiring talent, or maybe even paying off investors? Google has been working on the semantic web for years, though, so maybe 2011 will bring some fire starting that won’t fizzle.
Alice Wasielewski, January 5, 2011
Content Tagging Costs
December 27, 2010
We read an interesting blog post called “The Search for Machine-Aided Indexing: Why a Rule-Based System is the Cost-Effective Choice.” Information about the costs of indexing content using different methods is often difficult to locate.
The article provides some useful information; however, I always verify any dollar estimates. Vendors often do custom price quotations, which makes it difficult to compare certain products and services.
Here’s the passage that caught my attention:
The database company manager could not give an exact figure for what their final actual costs were for purchasing Nstein; however, she did state that it was “not cheap.” She admitted that it was more expensive than all of the other MAI software products that they considered. (A press release from Nstein reported that the deal was worth approximately $CAN 450,000). When asked about staffing requirements, the manager estimated that it took the time of five full-time indexers and two indexing managers about a “month or so” at first. She added that there is a need for “constant” (she then rephrased that to “annual”) training. The investment company manager preferred not to discuss the actual implementation costs of Nstein, as there was a good deal of negotiation with non-cash assets involved. (A press release from Nstein of March 14th, 2002 reported that the deal was a five-year deal valued at over $CAN 650,000).
I downloaded this write up and tucked it in my Search 2011 pricing file. One never knows when these types of estimates will come in handy. I noticed on a LinkedIn threat relating to enterprise search that a person posted prices for the Google Search Appliance. I did a bit of clicking around and tracked down the original source of the data: SearchBlox Software. The data on the chart reported prices for the Google Mini. When one explores the US government’s price list for Google appliances that can handle 20 million documents which is a count encountered in some search applications, the cost estimates were off by quite a bit. Think in terms of $250,000, not $3,000.
I use whatever pricing data is available via open source research, and I know that hard data are often difficult to locate. The “appliance” approach is one way to control some costs. The “appliance” is designed to limit, like an iPad, what the user can do. Custom installations, by definition, are more expensive. When rules have to be created for any content processing system, the costs can become interesting.
Stephen E Arnold, December 27, 2010
Freebie, although Access Innovations has bought me one keema nan several weeks ago.
Arnold Comments about Exalead
December 20, 2010
A couple of times a year, I make a swing through Europe. I visit vendors, get demos, and talk with engineers about the future of search. In Paris on November 30, 2010, I answered questions about my views of Exalead. As you know, Exalead is a unit of Dassault Systems, one of the most sophisticated engineering firms in the world. You can get my view of Exalead by navigating to this link. Here’s an example of the observations I made:
“Exalead delivers applications that fit seamlessly and smoothly into customer workflows,” said Arnold. “When I spoke with Exalead customers I heard only: ‘This system works,’ ‘It’s easy to use,’ ‘It’s stable,’ and ‘I don’t have to chase around.”
In the interview, I point out that Exalead’s engineering makes it possible to embed search and information access in applications. Instead of using key words to unlock the information in a traditional search and retrieval system, Exalead makes the needed information available within existing work flows and applications. Access extends across a full range of content types and devices, including smart phones.
I have tracked Exalead for a number of years, and it continues to distinguish itself in information access by going “Beyond Search.” Here at Beyond Search we use the Exalead platform for our Overflight service.
Stephen E Arnold, December 20, 2010
The Exalead engineering team bought me lunch, a plus in Paris. Too bad about the snow and ice, though.
Best Buy Big Box Goes Semantic
December 1, 2010
I have a distant recollection that Best Buy had two ways to present prices. One way was the public Web site and the other way was the information available in the store. That’s one of those semiotic moments that keep me from visiting the big box behemoth.
Best Buy is using the Semantic Web in some remarkable ways to harness data from their website. The article “The Semantic Web Delivers For Best Buy. So Why Not For Your Business, Too?” points out various ways that Best Buy uses data to improve customer experiences, both on their website and in their retail stores.
Best Buy has over 600,000 products available online, however the majority of online sales come from a small portion of those products. By using Semantic Web technologies, Best Buy can make some of the lesser known products come to the forefront in customer searches.
In addition, the company has started using a Semantic Web plug-in on their local store blogs that will “grab data about the SKU, plug in the Open Box price and the reason returned, and publish it to the site, usually on a weekly basis.” This effort has shown an increase in customers arriving at physical stores looking for Open Box products. Best Buy is at the forefront of these technologies and continues to find new ways to use them. How will other companies emulate this success? A starting point is one set of prices.
Laura Amos, December 1, 2010
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MediaBriefing and Semantics
October 18, 2010
At a recent conference, a person mentioned the site, www.mediabriefing.com. I took a look at it and found its coverage on point. I am not too interested in the media sector, preferring to track the foibles and follies of search and content processing system vendors.
What did catch my attention was “New Site — and Semantic Technologies — May Help The Publishing Industry Sail To The New Media World.” The story reported:
Here’s where the semantic part comes in at TheMediaBriefing.com: It uses core aspects of idio’s semantic web technology to find, classify, tag, and index these sources to deliver to readers in the media industry what TheMediaBriefing.com says are very accurate matches to their information needs. Brown’s background in blogging, and searching and curating various sources of news pertaining to the media, led him to the conclusion that getting hold of and coalescing the data you really needed often involved following a big trail that combined everything from news sites to social media to non-traditional outlets that his peers didn’t always themselves think to go to.
I don’t have much detail about the semantic system in use, but I think the idea is a good one. If the write up is on the money, the notion of a news operation relying on semantic technology is an interesting use case.
Several observations:
- Big dog publishers like LexisNexis have been ankle deep in semantic technology and other content technologies for many years. The problem is that the financial situation at some big dogs is challenging. Semantic technology may not be the tow truck needed to drag the companies back from the brink.
- Semantic technology, as I have suggested, works best as plumbing. Will publishers and readers realize that semantic technology is behind the new site. My hunch is that some may; others will not.
- Publishing as an industry is experimenting with new partners and different business models. The good news is that some of the partners are tech savvy. The bad news is that some of the business models don’t generate the margins that the old business models did. Semantic technology may not be able to change the bad news into good news quickly enough.
Check out the links in this article. Interesting stuff.
Stephen E Arnold, October 18, 2010
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Cognition Grabs Grabbit
October 15, 2010
We learned that Cognition Technologies has landed a deal with Grabbit, the developer of cloud hosted services for social media.
Cognition’s semantic tools will add zing to Grabbit’s new Web services. The scope of Cognition’s Semantic Map is more than double the size of any other computational linguistic dictionary for English, and includes more than ten million semantic connections that are comprised of semantic contexts, meaning representations, taxonomy and word meaning distinctions. The Map encompasses over 540,000 word senses (word and phrase meanings); 75,000 concept classes (or synonym classes of word meanings); 8,000 nodes in the technology’s ontology or classification scheme; and 510,000 word stems (roots of words) for the English language. Cognition’s lexical resources encode a wealth of semantic, morphological and syntactic information about the words contained within documents and their relationships to each other.
According to “Cognition to Power Grabbit’s Online Recommendation Engine”:
By using Cognition’s state-of-the-art semantic technology to analyze Tweets, Facebook updates, blog posts, friends, locations, product purchases, brand preferences, and other data, Grabbit will be able to intelligently recommend products, content, and people that a Grabbit user might find interesting.
For more information about Grabbit, Inc., navigate to Grabbit.net. For more information about Cognition Technologies, click to www.cognition.com.
Stephen E Arnold, October 15, 2010
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