Daniel Sparks of The Motley Fool reported, “”Chinese companies are starting to dream,” said early investor in Baidu (NASDAQ: BIDU ) and managing partner at GGV Capital Jixun Foo. Foo’s proclamation was made in an in-depth article by MIT Technology Review, which examined the Chinese search giant’s new effort to change the world with artificial intelligence. The company’s new AI lab does, indeed, accompany some lofty aspirations — ones big enough to hopefully help Baidu become a global Internet powerhouse and to compete with the likes of Google in increasingly important emerging markets where the default search engine hasn’t yet taken the throne. But what are the implications for investors? Fortunately, Baidu’s growing infatuation with AI looks like it could give birth to winning strategies that could build sustainable value over the long haul.”
Posts Tagged ‘search’
Semantic data integration vendor TopQuadrant’s TopBraid Suite 4.5 just hit the street, a major release that CMO and VP of Professional Services Robert Coyne says “provides a large number of new and enhanced capabilities driven primarily by customers who are using our TopBraid Enterprise Vocabulary Net solution for vocabulary and/or metadata management, or using TopBraid Live to create a custom, model-driven solution.”
The latest version, he says, features more business user and enterprise readiness-motivated improvements than any past major release since Release 4.0, when the current generation of the TopBraid EVN product was first introduced. Many of the enhancements were inspired by requests coming from different customers using TopBraid in different contexts, he notes.
New capabilities in EVN range from improved configurability for the EVN Ontology Editor, via a form builder that allows browser window management and enables users to open multiple view forms, tree and chart windows, to an improved search form that makes it possible to search on cardinalities, regular expressions, aggregates in the search counts and chart results.
Also part of the upgrade is increased support for business stakeholders who need to collaborate on defining and linking enterprise vocabularies, taxonomies and metadata used for information sharing, data integration and search. Features like that reflect the fact that a growing number of enterprise customers and business users are looking to leverage products such as TopBraid EVN, Coyne says.
Context is king – at least when it comes to enterprise search. “Organizations are no longer satisfied with a list of search results — they want the single best result,” wrote Gartner in its latest Magic Quadrant for Enterprise Search report, released in mid-July. The report also says that the research firm estimates the enterprise search market to reach $2.6 billion in 2017.
The leaders list this time around includes Google with its Search Appliance, which Google touts as benefitting from Google.com’s continually evolving technology, thanks to machine learning from billions of search queries. Also on that part of the quadrant is HP Autonomy, which Gartner says is “exceptionally good at handling searches driven by queries that include surmised or contextual information;” and Coveo and Perceptive Software, both of which are quoted as offering “considerable flexibility for the design of conversational search capabilities, to reduce the ambiguity of results.”
Schemaless structured document search system SIREn (Semantic Information Retrieval ENgine) has posted some impressive benchmarks for a demonstration it did of its prowess in searching complex nested documents. A blog here discusses the test, which indexed a collection of about 44,000 U.S. patent grant documents, with an average of 1,822 nested objects per doc, comparing Lucene’s Blockjoin capability to SIREn.
The finding for the test dataset: “Blockjoin required 3,077MB to create facets over the three chosen fields and had a query time of 90.96ms. SIREn on the other hand required just 126 MB with a query time of 8.36ms. Blockjoin required 2442% more memory while being 10.88 times slower!”
SIREn, which was launched into its own website and community as part of SindiceTech’s relaunch (see our story here), attributes the results to its use of a fundamentally different conceptual model from the Blockjoin approach. In-depth tech details of the test are discussed here. There it also is explained that while the focus of the document is Lucene/Solr, the results are identically applicable to ElasticSearch which, under the hood, uses Lucene’s Blockjoin to support nested documents.
The Semantic Web Blog also checked in with SindiceTech CEO Giovanni Tummarello to get a further read on how SIREn has evolved since the relaunch to enable such results, and in other respects.
Enterprise videos– visionary statements, product introductions, town hall meetings, training aids, and conferences – are everywhere on the Internet and corporate Intranets. But no matter how flashy the graphics or how well-prepared the speaker, there’s something missing when it comes to the viewer experience: The ability to search these videos.
Ramp is one of the vendors aiming to address the issue by delivering a fully automated data-driven user experience around finding content. It’s about the ability to watch and look inside a video — a 45-minute keynote, for example, said Joshua Berkowitz, the company’s director of product management at Enterprise Search & Discovery 2014. Everyone has had the experience of starting to view such an event online, only to get distracted by their smartphones or something else a few minutes in. In the meantime, the video plays on and goes right past the part you were most interested in without your even noticing. “How to find the piece of content that interests you in the same way you could find those pieces inside a document?” he asked the audience.
More importantly, how can the supplier of that content facilitate that, as well as other ways to help the viewer interact with the elements they are interested in, or provide additional information such as links to product or contact details? “Time-based metadata for video can revolutionize the search experience,” Berkowitz said, a capability Ramp’s technology supports with its MediaCloud technology that generates time-coded text transcripts and metadata from video content, providing a time-coded transcript and tag set.
There’s one thing that Tom Reamy, chief knowledge architect at KAPS Group, says is a continual refrain among enterprise business users: Search sucks. IT regularly attempts to make things better by buying new search engines and for awhile, everything’s good – until content grows and things start to go downhill again.
Enterprise search, he explained to an audience at this week’s Enterprise Search & Discovery summit, “is never going to be solved by search engine technology” alone. It needs a helping hand from a number of different corners to improve the experience. Good governance and taxonomies can help, for example. But there are challenges in their use, such as the fact that the people who write documents for enterprise repositories can be very creative at avoiding tasks they don’t consider their jobs, such as categorizing documents for others to find during their searches, and even if they’re willing to do it, figuring out what a document is about is a very complex decision.
And, as beautiful a structure as a taxonomy may be to behold, marrying it to millions of documents is itself complex in scale and purpose for both authors and librarians who may have had nothing to do with its creation and so can’t be counted on to apply it well.
Less recognized for the role it can play in rescuing enterprise search is text analytics.
A couple of weeks back The Semantic Web Blog reported on research from SEO optimization vendor Searchmetrics about the virtues of semantic markup. Now the 2014 Content Search Marketers Survey, which recently came out from enterprise SEO platform vendor Brightedge, adds some more interesting statistics to show about what matters to optimized search.
Among them: Half of the respondents consider a page/content-based approach to driving page traffic, conversions and revenue as being much more important for SEO in 2014 than in 2013. Another 50 percent said it would be more or as important this year than last.
“The page-based approach to SEO in the world of secure search is important for 100 percent of SEOs, and 85 percent stated that it would be more or much more important for them in 2014,” the report states. “SEOs are also still focused on the business impact of the keyword (90 percent), though the shift in focus to the page leaves only 50% percent stating that measuring the business impact of the keyword will be more important in 2014.”
Search, Content Analytics, Structured Data Management Have Hand In Growth Of WorldWide Software Market
IDC this week released the latest results from its Worldwide Semiannual Software Tracker, which provides total market size and vendor share for all software technology areas. In 2013, the tracker reports, the worldwide software market grew 5.5 percent year over year to a total market size of $369 billion.
None of the three primary segments that comprise the total software market in IDC’s software taxonomy – Applications; Application Development & Deployment (AD&D); and Systems Infrastructure software – had a standout performance, it says.
But function-specific types of software in these primary segments did. Among these headline acts, the Content Applications subset of the Applications primary market segment had year-over-year growth rates above 10 percent. That market, IDC says, is driven by Search and Content Analytics applications, which grew at 13.2 percent year over year. The Big Data and analytics adoption trend was largely responsible for this market growth, it says.
MindMeld – you may know the term best from StarTrek and those fun-loving Vulcan practices. But it lives too at Expect Labs, as an app that listens to and understands conversations and finds relevant information within them, and as an API that lets developers create apps that leverage contextually-driven search and discovery – and may even find the information users need before they explicitly look for it.
Anticipatory computing is the term Expect Labs uses for that. “This is truly a shift in the way that search occurs,” says director of research Marsal Gavaldà. “Anticipatory computing is the most general term in the sense that we have so much information about what users are doing online that we can create accurate models to predict what a user might need based on long-ranging history of that user profile, but also about the context.”
The more specific set of functionality that contributes to the overarching theme of anticipatory computing, he explains, “means that you can create intelligent assistants that have contextual search capabilities, because our API makes it very easy to provide a very continuous stream of updates about what a user is doing or where a user is.”
Gartner recently released its report dubbed, “Cool Vendors in Supply Chain Services,” which gives kudos to providers that use cloud computing as an enabler or delivery mechanism for capabilities that help enterprises to better manage their supply chains.
On that list of vendors building cloud solutions and leveraging big data and analytics to optimize the supply chain is startup Elementum, which The Semantic Web Blog initially covered here and which envisions the supply chain as a complex graph of connections. As we reported previously, Elementum’s back-end is based on a real-time Java, MongoDB NoSQL document database and flexible schema graph database to store and map the nodes and edges of a supply chain graph. A URI is used for identifying data resources and metadata, and a federated platform query language makes it possible to access multiple types of data using that URI, regardless of what type of database it is stored in. Mobile apps provide end users access to managing transportation networks, respond to supply chain risks, and monitor the health of the supply chain.
Gartner analyst Michael Dominy writes in the report that Elementum earns its cool designation in part for its exploitation of Gartner’s Nexus of Forces, which the research firm describes as the convergence and mutual reinforcement of social, mobility, cloud and information patterns that drive new business scenarios.
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