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Category: Search & Semantic Tech (page 1 of 39)

Gilbane Advisor 3-19-19 — Federated ML, ephemeral messaging, search for humans

Google releases federated machine learningTensorFlow summit 2019

Federated learning is going to be a thing. Health care is just one example… “TensorFlow Federated will provide distributed machine learning for developers to train models across many mobile devices without data ever leaving those devices. Encryption provides an additional layer of privacy, and weights from models trained on mobile devices are shared with a central model for continuous learning.” Read More

A warning on the dangers of ephemeral messaging

The Information’s Sam Lessin is bullish about Facebook’s moving to full encryption, but thinks a reliance on ephemeral messaging is a big mistake. He makes a good case and the issues he raises need broader consideration. (Firewall – but you can get access by providing an email.) Read More

Search engines: a human perspective

Wise words on search applications from Daniel Tunkelang.

The foundation of human-computer information retrieval (HCIR) is that search engines help searchers who help themselves. The best search engines reward searchers’ incremental effort with a higher return on investment. … But searchers have been trained by simple search interfaces, and their laziness is compounded by a skepticism of anything that violates their expectations. In order to earn searcher effort, search engines have to provide simple, incremental, and effective steps that guide searchers — and that teach them through experience that the return justifies the additional effort. Read More

Facebook’s News Feed era is now officially over

It’s anyone’s guess where Facebook will end up after the strategic shift announced last week. The new direction impacts all parts of the company and raises questions about their business model, growth, and of course, organization. Read More


Join us at Gilbane’s Digital Experience Conference

Digital experience strategies, technologies, and practices, for marketing and the workplace

Also…

The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

Speaker Spotlight: John Felahi – Making content findable

In another installment of Speaker Spotlight, we posed a couple of our frequently asked questions to speaker John Felahi, Chief Strategy Officer at Content Analyst Company, LLC. We’ve included his answers here. Be sure to see additional Speaker Spotlights from our upcoming conference.

John_Felahi-horiz

Speaker Spotlight: John Felahi

Chief Strategy Officer

Content Analyst Company, LLC

 

What is the best overall strategy for delivering content to web, multiple mobile, and upcoming digital channels? What is the biggest challenge? Development and maintenance cost? Content control? Brand management? Technology expertise?

One of the biggest challenges to delivering content to the web is making it as findable as possible to potential interested viewers.  While traditional, manual tagging and keyword search methods may have gotten us this far, and may be good enough for some use cases, they’re still not without limitations. The good news is, there are far more advanced, sophisticated – and automated – technologies available to remedy the numerous limitations of manual tagging content and keyword-based search. The limitations of manual tagging and keyword-based include:

  • Term creep – New terms constantly emerge, requiring taxonomies to be constantly updated.
  • Polysemy – Take Apple, for example. Is your user searching for the company, the Beatles’ record label, or the fruit?
  • Acronyms – Texting has introduced an entirely new language of acronyms (LOL, TTYL, WDYT).  Manually tagging content requires the editor to consider possible acronyms the users will be searching for.
  • Abbreviations – Tagging content with long, scientific terms, geographies, etc. require editors to factor these in along with the long terms they represent.
  • Misspellings – Thanks to spellcheck and autocorrect, technology has become much more forgiving for those who never made it past the first round eliminations in their sixth grade spelling bee. Content search, unfortunately, needs to be equally accommodating, if you want your users to find your content – which means tagging it with common misspellings.
  • Language – The web has certainly made the world a much smaller place, but that doesn’t mean everyone speaks English.  Making content findable in any language means it has to also be tagged in multiple languages.

On to the good news – there’s technology that’s been used for years in eDiscovery and the US Intelligence Community to overcome these very challenges, but for different reasons. Because the bad guys aren’t tagging their content to make it more findable, the intel community needs a better way to find what they’re looking for. And in eDiscovery, finding relevant content can make a multi-million dollar difference to the outcome of a particular litigation or other regulatory matter. That’s why tens of thousands of legal reviewers and countless analysts in the intel community use a technology known as concept-aware advanced analytics.

How concept-aware advanced analytics differs from manual tagging and keyword search

As its name implies, concept-aware understands the underlying concepts within the content. As such, it can tag content automatically.  On the viewer’s side, content can be found by simply saying, “find more like this.” Categories are defined by taking examples that represent the concepts of a category. The system “learns” what that category is all about, and can then identify conceptually similar content and apply the same category. The process is the same on the search side. The user points to a piece of content and says, “find more like this.” Or as the content publisher, you present the viewer with conceptually similar content, i.e., “you may also be interested in these articles.”

While concept-aware advanced analytics doesn’t necessarily replace manual tagging and keyword search – which work very well in certain situations – the technology clearly overcomes many of the limitations of traditional tagging and search methods.

Catch Up with John at Gilbane

Track E: Content, Collaboration, and the Employee Experience

E7: Strategic Imperatives for Enterprise Search to Succeed
Wednesday, December, 4: 2:00 p.m. – 3:20 p.m.

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HP to Acquire Autonomy

HP and Autonomy Corporation announced the terms of a recommended transaction under which HP will acquire all of the outstanding shares of Autonomy for £25.50 ($42.11) per share in cash. The transaction was unanimously approved by the boards of directors of both HP and Autonomy. The Autonomy board of directors also has unanimously recommended its shareholders accept the Offer. Based on the closing stock price of Autonomy on August 17, 2011, the consideration represents a one day premium to Autonomy shareholders of approximately 64 percent and a premium of approximately 58 percent to Autonomy’s prior one month average closing price. The transaction will be implemented by way of a takeover offer extended to all shareholders of Autonomy. A document containing the full details of the Offer will be dispatched as soon as practicable after the date of this release. The acquisition of Autonomy is expected to be completed by the end of calendar 2011. Founded in 1996, Autonomy is a provider of infrastructure software for the enterprise with a customer base of more than 25,000 global companies. Positions HP as leader in large and growing space‚Äî Autonomy has a strong position in the $20 billion enterprise information management space, which is growing at 8 percent annually and is uniquely positioned to continue growth within this space. Furthermore, key Autonomy assets would provide HP with the ability to reinvent the $55 billion business analytics software and services space, which is growing at 8 percent annually. Reasons for the acquisition were cited as‚Äî Complements HP’s existing technology portfolio; Provides differentiated IP for services and extensive vertical capabilities in key industries; Provides IPG a base for content management platforms; Enhances HP’s financial profile; as well as Autonomy should be accretive to HP’s earnings. http://www.hp.com/ http://www.autonomy.com/

Endeca Now Integrates Hadoop

Endeca Technologies, Inc., an agile information management software company, announced native integration of Endeca Latitude with Apache Hadoop. Endeca Latitude, based on the Endeca MDEX hybrid search-analytical database, is uniquely suited to unlock the power of Apache Hadoop. Apache Hadoop is strong at manipulating semi-structured data, which is a challenge for traditional relational databases. This combination provides flexibility and agility in combining diverse and changing data, and performance in analyzing that data. Enabling Agile BI requires a complete data-driven solution that unites integration, exploration and analysis from source data through end-user access that can adapt to changing data, changing data sources, and changing user needs. Solutions that require extensive pre-knowledge of data models and end-user needs fail to meet the agility requirement. The united Endeca Latitude and Apache Hadoop solution minimizes data modeling, cleansing, and conforming of data prior to unlocking the value of Big Data for end-users. http://www.endeca.com/ http://hadoop.apache.org/

Sophia Launches Sophia Search for Intelligent Enterprise Search and Contextual Discovery

Sophia, the provider of contextually aware enterprise search solutions, announced Sophia Search, a new search solution which uses a Semiotic-based linguistic model to identify intrinsic terms, phrases and relationships within unstructured content so that it can be recovered, consolidated and leveraged. Use of Sophia Search is designed to minimize compliance risk and reduce the cost of storing and managing enterprise information. Sophia Search is able to deliver a “three-dimensional” solution to discover, consolidate and optimize enterprise data, regardless of its data type or domain. Sophia Search helps organizations manage and analyze critical information by discovering the themes and intrinsic relationships behind their information, without taxonomies or ontologies, so that more relevant information may be discovered. By identifying both duplicates and near duplicates, Sophia Search allows organizations to effectively consolidate information and minimizing storage and management costs. Sophia Search features a patented Contextual Discovery Engine (CDE) which is based on the linguistic model of Semiotics, the science behind how humans understand the meaning of information in context. Sophia Search is available now to both customers and partners. Pricing starts at $30,000. http://www.sophiasearch.com/

Federated Media Acquires Technology Suite from TextDigger

Federated Media Publishing, a “next-generation” media company, announced the acquisition of a platform for semantic and linguistic profiling of web-based content from TextDigger, a San Jose-based semantic search startup. FM provides a full suite of media and marketing services for brand advertisers that depends heavily on a proprietary media and marketing technology platform. TextDigger’s technology complements FM’s platform with a set of semantic solutions for content tagging, filtering and clustering, as well as related tools that enhance the user experience, ad targeting, and semantic search engine optimization for a site. TextDigger will continue its search business, all of TextDigger’s customers will continue to be supported by either FM or TextDigger, depending on the type of project or service. www.federatedmedia.net www.textdigger.com

Open Text to Acquire Nstein

Open Text Corporation (NASDAQ:OTEX) (TSX: OTC) and Nstein Technologies Inc. (TSX-V: EIN) announced that they have entered into a definitive agreement by which Open Text will acquire all of the issued and outstanding common shares of Nstein through an Nstein shareholder-approved amalgamation with a subsidiary of Open Text under the Companies Act (Québec). Based on the terms of the definitive agreement, Nstein shareholders will receive for each Nstein common share, CDN $0.65 in cash, unless certain eligible shareholders otherwise elect to receive a fraction of an Open Text TSX traded common share, having a value of CDN $0.65 based on the volume weighted average trading price of Open Text TSX traded common shares in the 10 trading day period immediately preceding the closing date of the acquisition. This purchase price represents a premium of approximately 100 percent above the 30 trading day average closing price of Nstein’s common shares. The transaction is valued at approximately CDN $35 million. Based in Montreal, Nstein’s solutions are sold across market segments such as media and information services, life sciences and government. The transaction is expected to close in the second calendar quarter and is subject to customary closing conditions, including approval of two-thirds of the votes cast by Nstein’s shareholders and applicable regulatory and stock exchange approvals. A special meeting of Nstein’s shareholders is expected to be held to consider the amalgamation in early April, 2010. http://www.opentext.com, http://www.nstein.com

Contegra and dtSearch Announce Faceted Search for dtSearch

Contegra Systems and dtSearch announced a faceted search add-on for dtSearch Developer Customers. Faceted search enables dynamic filtering of search results by attributes. Built on the dtSearch Engine APIs, Contegra Systems’ Kaleido Search now makes faceted search available to content-rich applications and e-commerce sites. Kaleido Search offers the ability to group search results by facet, the ability to “expand and collapse” facet selections, on-demand summaries of selected facets, and more. Kaleido Search enables these faceted search features in the context of comprehensive solution for online data access that is customizable to suit any site. The dtSearch Engine can index over a terabyte of data in a single index, as well as create and instantly search an unlimited number of indexes. The software offers more than 25 search options, including Unicode support covering hundreds of international languages. Proprietary file format support highlights hits in popular file types.  A built-in Spider supports searching of local and remote, public and secure, dynamic and static web data, with WYSIWYG hit-highlighted displays. The dtSearch Engine API supports .NET, Java, C++, SQL, etc., including native 64-bit Windows/Linux support. http://www.contegrasystems.com, http://www.dtsearch.com

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