Posts Tagged ‘enterprise search’

What’s The Word On Enterprise Search?

Photo Credit: Sean MacEntee/ Flickr

Photo Credit: Sean MacEntee/ Flickr

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.”

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Enterprise Search Doesn’t Have To Stink

reamyimgaeThere’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.

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New KDE Software Compilation Released with Improved Semantic Search

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According to a new article out of the organization, “The KDE Community is proud to announce the latest major updates to the KDE Applications delivering new features and fixes. Kontact (the personal information manager) has been the subject of intense activity, benefiting from the improvements to KDE’s Semantic Search technology and bringing new features. Document viewer Okular and advanced text editor Kate have gotten interface-related and feature improvements. In the education and game areas, we introduce the new foreign speech trainer Artikulate; Marble (the desktop globe) gets support for Sun, Moon, planets, bicycle routing and nautical miles. Palapeli (the jigsaw puzzle application) has leaped to unprecedented new dimensions and capabilities.” Read more

Artificial Intelligence Company Inbenta Receives $2M in Series A Funding

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Sunnyvale, CA (PRWEB) April 17, 2014 — Inbenta, the Semantic Search Engine provider, announces it has closed a $2M Series A funding from a group of investors led by “Amérigo Chile Early Stage and Growth”. Amerigo is an international network of technological Venture Capital funds which forms part of Telefónica’s commitment to boosting technological innovation around the world. Inbenta will use the funds to continue to scale out their A.I. based Semantic Search platform for enterprise customer care solutions while expanding operations worldwide. Read more

Semantic Search and the Data Center

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Haim Koshchitzky of Sys-Con Media recently wrote, “Enterprise applications can ‘live’ in many places and their logs might be scattered and unstandardized. First generation log analysis tools made some of the log data searchable, but the onus was on the developer to know what to look for. That process could take many hours, potentially leading to unacceptable downtime for critical applications. Proprietary log formats also confuse and confound conventional keyword search. That’s why semantic search can be so helpful. It uses machine intelligence to understand the context of words, so it becomes possible for a Google user to type ‘cheap flights to Tel Aviv on February 10th’ rather than just ‘cheap flights’ and receive a listing of actual flights rather than links to airline discounters. Bing Facebook, Google and some vertical search engines include semantic technology to better understand natural language. It saves time and creates a better experience.” Read more

Where Enterprise Search Was, And Where It Is

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Photo Courtesy Flickr/katieb50

Interested in discovering what’s happened to some of the enterprise search vendors that have piqued your interest in the past? You may want to head here, where enterprise search industry expert and author of the Enterprise Search Report Stephen E. Arnold of ArnoldIT is posting a series of profiles of firms that have tried and failed – or in some cases, still are trying to – make a business in enterprise search.

It’s not easy, Arnold writes: “Search is a very difficult problem to solve and turn into a sustainable business.”

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Make Enterprise Search Better For Users, And Better For IT

rsz_searchHow seamlessly are employees able to conduct searches for enterprise data?

According to a new survey from SearchYourCloud, not very. Some searches, it finds, take up to 25 minutes, and often users have to do 8 different queries until the right document is found. Only 1 in 5 searches come out with correct results the first time. “That’s appalling in this day and age,” says founder and CEO Simon Bain.

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PureDiscovery Raises $10M to Make Search More Like a Brain

Derrick Harris of GigaOM reports that PureDiscovery, a company we have covered in the past, has raised $10 million in Series C funding to reinvent enterprise search. Harris writes, “Rather than indexing documents and letting users perform keyword searches, PureDiscovery is focused on semantic technology and learning the concepts contained within a company’s content. We first covered PureDiscovery in early 2012, when the company was just beginning its push out of the legal field where it has already made a name for itself. The company’s software has proven effective in e-discovery, where it’s used to learn what’s contained within thousands of pages of documents turned over during litigation. PureDiscovery also powers patent search for LexisNexis, where it has analyzed hundreds of millions of patent documents and journal articles to surface the most-relevant content regardless of keyword relevancy.” Read more

Searchbox Wants To Help You Build Your Enterprise’s Specialized Search Engine

Searchbox is taking its enterprise semantic search technology in a new direction. The offering, which The Semantic Web Blog initially covered here, today is packaged as a software-as-a-service (SaaS) solution, and it’s now based on the Apache Solr open source enterprise search platform from the Apache Lucene project rather than on proprietary technology.

“We completely changed the technology stack for keyword search and integrated our semantic technology into Solr,” says chief product officer Jonathan Rey. On top of Apache Solr, he says, the company developed a search application framework that IT managers, CIOs, and developers can leverage to provide a richer experience to end users.

“There is no such thing as ‘standard enterprise search.’ Searchbox is a platform onto which companies can build a specialized search engine,” Rey says.

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Mindbreeze positioned as a “Challenger” in Gartner “Magic Quadrant for Enterprise Search”

Mindbreeze, a software provider for enterprise search and digital cognition, has been positioned as a “Challenger” in the Gartner “Magic Quadrant for Enterprise Search” 1). The evaluation is one of the most internationally influential market analyses for the evaluation of enterprise search software. The US analyst group analyses different providers based on criteria such as market penetration, innovation and strength of implementation and places them into the categories “Challengers”, “Leaders”, “Visionaries” and “Niche Players”. Read more

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