Ce diaporama a bien été signalé.
Nous utilisons votre profil LinkedIn et vos données d’activité pour vous proposer des publicités personnalisées et pertinentes. Vous pouvez changer vos préférences de publicités à tout moment.

The Path to Cognitive Search

85 vues

Publié le

The Path to Cognitive Search

Publié dans : Business
  • If we are speaking about saving time and money this site ⇒ www.WritePaper.info ⇐ is going to be the best option!! I personally used lots of times and remain highly satisfied.
       Répondre 
    Voulez-vous vraiment ?  Oui  Non
    Votre message apparaîtra ici

The Path to Cognitive Search

  1. 1. 5-Minute Guide The Path to Cognitive Search
  2. 2. 5-Minute Guide : The Path to Cognitive Search 2 The Path to Cognitive Search SEARCH HAS COME A LONG WAY Enterprise search was born in 1952, when H. P. Luhn of IBM first proposed the creation of an electronic information searching system.1 That same year saw the confirmation that DNA is genetic material. The advances in life sciences prompted by what we’ve learned about DNA are staggering. It’s comparably staggering to consider how search has changed and continues to evolve. The 2012 paper, “Cognitive Search: Evolution, Algorithms, and the Brain,” pinpoints the forces driving this evolution: “Search—the behavior of seeking resources or goals under conditions of uncertainty—is a common and crucial behavior for most organisms. It requires individuals to achieve an adaptive trade-off between exploration for new resources distributed in space or time and exploitation of those resources once they are found.” 2 Viewed through the lens of uncertainty and time, early enterprise search concentrated on reducing uncertainty, developing powerful full-text retrieval capabilities. Answers came in the form of pages of result-documents, ranked by their relevance to query- terms. And, at least initially, response time wasn’t critical. As organizations deployed search technology to organize and retrieve their knowledge management and intranet assets, they quickly recognized that fixed relevance formulas produced sub-optimal answers. The experience of early market leader Inktomi 3 illustrates how failing to recognize the link between relevance and the reduction of uncertainty could open the door for disruption. 5-Minute Guide 1 http://www.altaplana.com/Semantic+Web3.0-SG-EN.pdf 2 “Cognitive Search: Evolution, Algorithms, and the Brain,” edited by Peter M. Todd, Thomas T. Hills, and Trevor W. Robbins. 2012. Strüngmann Forum Report, vol. 9, J. Lupp, series ed. Cambridge, MA:MIT Press. ISBN 978-0-262-01809-8. 3 https://searchenginewatch.com/sew/news/2173677/google-beat-inktomi-inside-story-engineer 45% of surveyed organizations plan to replace existing search technology between 2016 and 2018. – Findwise 2016
  3. 3. 5-Minute Guide : The Path to Cognitive Search 3 Putting Value on Relevance and Simplicity Google.com first registered as a domain on September 15, 1997. Co-Founders Larry Page and Sergey Brin envisioned monetizing information on the Web, and they needed to improve relevance to make their business model click. Their first step: create a tunable relevance calculation with many parameters, including user interaction with the list of results. Several search technology vendors, such as FAST and Endeca, recognized the opportunity as well, and implemented tunable relevance capabilities. More relevant results reduced the uncertainty inherent in search, increasing value for customers and vendors alike. Google also made it easier to find things, even if you knew nothing about query languages or Boolean expressions. A simple, keyword input box coupled with sophisticated, behind-the-scenes query processing made everyone a more confident search professional. With these innovations, confidence displaced uncertainty and simplicity reduced the time spent searching. Value increased for customers and vendors. Users didn’t care about the science behind relevance. They just knew that search was faster and the results were better. Naturally, expectations for speed and accuracy increased. Google’s performance set the standard. Less time and energy spent searching with better results. Search entered its Golden Age. SEARCH MEETS BIG DATA Steven Nicolaou, principal consultant with Microsoft, notes that from 2008 through 2012, big companies acquired smaller search vendors like FAST Search and Transfer to gain innovative search technology.4 These smaller companies benefited from surpassing the expectations Google created, pushing the breadth and depth of search-driven applications. Over those four years, dominant market players acquired virtually every small, innovative technology vendor and integrated their capabilities into an enterprise software stack. 4 http://www.docurated.com/enterprise-search/enterprise-search-14-industry-experts-predict-future-search 30% of enterprise search queries will start with a “what,” “who,” “how,” or “when” by 2018. – Gartner Inc. 2015
  4. 4. 5-Minute Guide : The Path to Cognitive Search 4 During this consolidation, new sources and uses of information emerged as potent disruptive forces. Nicolaou observes that as the cost of storage decreased, despite soaring data volumes, it became cheaper (and faster) to use search rather than data curation to finding the right answers.5 As a result, the era of Big Data – with its volume, velocity, and variety – initiated a new disruption. An essential element in that disruption was the equal importance of structured (typically numerical, database-resident) and unstructured data (including text and streaming) data to develop better insights. The ability to correlate and search across disparate information types further differentiated emerging search solutions from earlier enterprise and open source search platforms. Search had become semantic. WHAT DO WE REALLY WANT FROM SEARCH? Today, no one wants a term paper reading list for a search result. If computers can beat humans at chess and televised trivia contests, is it any wonder users expect more concise, relevant answers from search? And, with succinct, relevant answers, users need confidence that refining or extending their search will improve answer quality. If we spend more time searching, we expect greater confidence in the answers. Whether it’s searching for information or a pair of glasses, we want to find it quickly so we can use it. As Ambient Findability author Peter Morville says, “Findability precedes usability.” Users accustomed to mobile devices also want to access search in a more natural manner. That expectation is disrupting the traditional search interface. Ron Kaplan’s article in Wired outlined the case for a conversational user interface: 6 The graphical interface … is beginning to fray around the edges. We’re now grappling with an unintended side effect of ubiquitous computing: a surge in complexity that overwhelms the graphical-only interface. It can take as many as 18 clicks on 10 different screens to make one simple airline reservation while we’re faced with an unwieldy array of buttons, ads, drop-downs, text boxes, hierarchical menus and more. [Conversation] …is the interface of the future, made even more necessary as computing propagates beyond laptops, tablets and smartphones to cars thermostats, home appliances and now even watches … and glasses. Conversation is more than just speech recognition; it’s the iterative process human’s use to discover and learn. 7 5 Ibid. 7 https://www.wired.com/2013/03/conversational-user-interface/ 51% of surveyed organizations report user communities that are “dissatisfied” or “very dissatisfied” with existing search solutions. – Findwise 2016 6 http://findability.org/archives/cat_findability.php
  5. 5. 5-Minute Guide : The Path to Cognitive Search 5 The things we really want from search—contextual relevance, convenience, and confidence—are the same objectives that have spawned cognitive search. WHAT IS COGNITIVE SEARCH AND WHAT CAN IT DO? Cognitive search refers to a collection of search capabilities that increase relevance, convenience, and confidence, with repeated use. For each of those capabilities, improvement, or learning with repeated use is what makes the capability cognitive. Forrester’s definition of cognitive search captures this point: Financial services institutions have been among the most enthusiastic adopters of cognitive search-based applications. With their use of natural language processing, machine learning and semantic analysis, financial institutions manage and monitor the volume, variety, velocity, and ambiguity commonly associated with global, 7x24 operations. In an operational context where time is literally money, delivering relevance, convenience, and confidence determines winners and losers. Discovery and analytical tools that leave data in place can mitigate security and privacy concerns. Likewise, tools that don’t override whatever rules or policies apply to regulated data allow a managed self-service model that leaves IT with the control it needs to ensure security and compliance. Examples of capabilities that have cognitive potential include machine-learning (including both supervised (classification) and unsupervised (clustering) methods), statistical pattern recognition, natural language processing and dialogue, and ontological reasoning. Setting aside the technical details each involves, these cognitive technologies support one or more of five activities. Indexing, natural language processing, and machine-learning technologies combined to create an increasingly relevant corpus of knowledge from all sources of unstructured and structured data that use naturalistic or concealed query interfaces to deliver knowledge to people via text, speech, visualizations, and/or sensory feedback. 8 8 Brief: Cognitive Search Is Ready To Rev Up Your Enterprise’s IQ, Rowan Curran and Mike Gaultieri, Forrester, May, 2016
  6. 6. 5-Minute Guide : The Path to Cognitive Search 6 3 http://vmblog.com/archive/2015/11/05/zoomdata-2016-prediction-big-data-analytics-anywhere-in-2016.aspx#.WDxV_YXfUi3 Psychologists and technologists agree that cognition involves: 1. Transforming sensory/data inputs into understandable formats 2. Reducing massive amounts of data to a concise, usable summary 3. Elaborating, extending, and enriching the information processed 4. Storing and recovering information efficiently 5. Using information to solve a meaningful problem Add the capacity for continual learning and improvement to these activities and you have an accurate picture of where cognitive search begins and what it has to offer. UPGRADING TO COGNITIVE SEARCH Massive declines in the cost of storage and computation have finally made cognitive computing economical. With the emergence of these methods from academia, organizations now have access to tools, solutions, and platforms that can deliver a better experience finding and discovering new insights. The focus has shifted to accelerating time-to-value in the deployment of cognitive search. Attivio’s cognitive search solution delivers insight and innovation, providing market leaders with a platform that scales efficiently and operates securely and effectively. Leading, independent analysts rank Attivio as a leading provider of capabilities spanning search, knowledge discovery, and text analytics. With its ability to comprehensively catalog every relevant information source, enrich every cataloged object, and deliver secure results to applications and tools from an agile, extensible platform, Attivio makes searching cognitive.
  7. 7. 5-Minute Guide : The Path to Cognitive Search 7 Attivio is the leading cognitive search & insight company. Our Fortune 500 clients rely on us to drive innovation, operational efficiencies, and improve business outcomes. Our solutions provide industry-leading natural language processing, machine learning, analytics, and knowledge graphing capabilities at scale. Let Attivio empower you to act with certainty. For more information, please visit www.attivio.com.

×