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Perspectives on Text Analytics in 2009 | killexams.com real questions and Pass4sure dumps

You’re reading this article because you’re actively interested in text analytics technology and market trends. Whether you’re a solutions provider or consumer, you want to subsist sure you’ve invested your time and pecuniary resources wisely.

The picture is complex, however, as the text analytics domain is not dominated by any one algorithm or approach, vendor or traffic sector. So far, the diversity of options has benefitted potential users; awareness (and realization) of the technology’s capabilities is structure rapidly in areas such as media monitoring, publishing, customer-experience management and semantic search. Meanwhile, growth remains strong in domains that fill long applied text analytics. These areas comprise life sciences, intelligence and law enforcement, and pecuniary services. While the text analytics domain isn’t unaffected by current traffic conditions, economic pressures could actually spur uptake motivated by a quest for efficiency through automation.

Sources and Perspectives

To stay on top of trends, I try to talk to current and prospective users as often as I can, and I besides try to support up with researchers and fellow analysts. (You’ll find links for some of the folks I result at my BeyeNETWORK channel.) I besides catch up with vendors periodically.

Because it’s helpful to understand current industry perspectives, I recently invited CEOs, CTOs and thought leaders to respond to the following query:

What enact you remark as the 3 (or fewer) most well-known text analytics technology, solution or market challenges in 2009?

Before relaying answers I received, I’ll mention two meta-replies. First, Marti Hearst, associate professor in the UC Berkeley School of Information, declined to respond, in fragment because “…for me, 2009 is too near a time horizon.” This thought applies not only to academic researchers but besides to anyone who’s thinking strategically, beyond this year’s crop of product releases and traffic conditions. Next, Lexalytics CEO Jeff Catlin candidly characterized his response as “somewhat self-serving thoughts.” No doubt many of the vendors quoted remark the greatest challenges as residing in areas their tools address, so select their views with a grain of salt.

I’ll relay whole views with minimal editing, complete with vendor self-promotion because, after all, commercial products are “where the rubber hits the road” for most enterprise users.

Text Analytics in 2009

Let’s start with Maria Milosavljevic, CTO at Capital Markets Cooperative Research Centre, an Australian group that is conducting leading-edge R&D in real-time security-market surveillance. The top 3 for Maria are:

  • Expectations: Unfortunately I judge that the most difficult challenges of the past are still with us, and this is the biggest. People either believe that not much at whole is workable or they believe that more is workable than reality. It is never the case where quit users fill realistic expectations.
  • Portability: Text analytics systems trained on a particular type of input data enact not typically transfer well to other types of input. Cross-domain issues (e.g., from tidings to medical) are similar to transfer between intra-domain input documents (e.g., from medical tidings to medical journals).
  • Data quality: Data is never clean. Garbage in = garbage out!
  • Breck Baldwin of Alias-i, author of LingPipe natural language processing software, is very to-the-point in his reply, with a sort of twist on Maria’s expectations response.

    #1 thing the territory needs is a profound and real success memoir of text analytics.

    The reply from Sid Banerjee, CEO of Clarabridge, looks at factors related to scaling text analytics to the enterprise, “the expansion of text analytics across a few dimensions.” His reply:

  • From a functional to an enterprise imperative. In 2006-2008, text analytics was deployed to marketing, summon center, survey groups. Over the past few years, solutions fill morphed from those that serve one group to an offering that supports multiple groups, and now customers are looking, on day one, to pick solutions that can demonstrate cross-functional value. The selling cycles are more complex, the solutions necessity to exhibit more a priori traffic value and relevance, and at the selfsame time, because the solutions are not just deployed in one area, IT wants to know more how the solution is going to meet with "enterprise" standards. In total: selling is now more complex, more constituencies are involved in the decision, but at the selfsame time articulating and demonstrating traffic value is even more important.
  • From an isolated to an integrated solution. Toward the quit of 2008, they started seeing more interest from companies and partners looking to seamlessly integrate the results of text analytics back into operational systems, i.e., process customer verbatims and merge the categorized, scored results back into summon focus applications. This modern employ cycle – not just for analytics, but for operational integration – provides an inviting occasion for text analytics vendors to deem whether to subsist a stand-alone application or to be more tightly integrated with ally products and offerings.
  • From a static to a scalable architecture. The titanic memoir in 2008 was scale. Data volumes are going up. Usage requirements are going up. There's no judgement to expect scalability requirements won’t continue to grow in 2009 and beyond. The winners will subsist those who can remark beyond today's data and user volumes and design for an order or two more magnitude in their offerings, predicting this sure future.
  • Aaron B. Brown of IBM similarly looks at architectural issues and besides at traffic concerns. Aaron is Program Director, ECM Discovery, for IBM Information Management Software and has distinguished market and technical insights. I interviewed him eventual year on “Text Analytics for Legal Compliance.” That exchange is still a suitable read. Here are his thoughts on challenges for 2009:

  • Defining the traffic case for text analytics. In the current economic situation, organizations are clamping down on modern projects and more than ever looking for arduous ROI savings to warrant investment. To pass the funding bar, text analytics solutions, which typically plunge in the category of modern projects undertaken for traffic optimization, necessity to arrive with solid traffic cases that demonstrate hard-dollar operational savings based on proven examples. Given the emerging nature of many text analytics solution areas, this will subsist a challenge to growth in 2009.
  • Creating fully interactive exploratory analytics. Most current text analytics approaches reckon on extensive design-time configuration and customization. This has limited its applicability to employ cases where categories of extracted entities, etc. are understood up front. An emerging class of investigation-centric applications, such as eDiscovery, requires text analytics that can subsist rapidly and seamlessly reconfigured by the traffic analyst as they explore data sets and interactively refine their understanding of what needs to subsist extracted. Further, these applications add pressure to democratize text analytics, as the traffic user can no longer wait for a linguistic or data processing expert to reconfigure the analytics each time a modern insight is reached. The modern challenge for text analytics is to enable extraction and analysis that are near instantaneous and at the selfsame time are reconfigurable at interactive speeds by a traffic user without specialized text or linguistic expertise.
  • Expanding mainstream employ cases for text analytics. To date, text analytics has had strong traction in sure niche solution markets. However, it has yet to subsist widely adopted as a horizontal capability powering broad traffic optimization employ cases in content-centric (e.g., ECM), process-centric (e.g., BPM) or data-centric (e.g., BI) applications. As the market moves toward mainstream usage, text analytics technologies (and their relatives in text classification and search) will necessity to integrate more tightly into information and process management platforms – potentially being subsumed into them as indigenous capability – and solutions will shift to leveraging analytics in conjunction with broader information management and technologies. 2009 will subsist a faultfinding year for text analytics to start making this transition.
  • Other replies besides looked at traffic conditions and at experiences in the adoption and employ of text technologies. Lexalytics CEO Jeff Catlin foresees:

  • The penniless economy will shift the sale of text analytics to larger companies. We're already seeing this in their sales, which used to subsist about two-thirds small companies and one-third large companies. Now it's mostly larger companies. The upside of this is that titanic companies are spending on search and text analytics as they search to reclaim money and augment efficiency due to lower staffing levels.
  • Technical push: Their thrust this year is going to subsist on empowering the customers with easy-to-use linguistic tools that will allow users to build and deploy some of their own text analytics bits and pieces using their core frameworks. The first of these for us is a user-driven entity recognizer that will allow users to expense up domain-specific text (let’s issue medical text) with entities (diseases); and then after marking up a hundred or so stories, the system will build a "model" or recognizer for that type of entity so that it can deduce other diseases from how they’re described in the text. We'll subsist releasing their first version of this by late February/early March and hope to further enhance the tool over the course of the year to further empower the users. Their initial market research indicates that publishers/media would find such tools very valuable because of the amount of time/money they spend on maintaining lists.
  • I expect the number of vendors to shrink as those with weaker or narrower offerings find it increasingly difficult to sell in this very challenging environment. To accomplish a depart of it in 2009, it seems that at a minimum, vendors necessity to provide: entity extraction, concept extraction and possibly sentiment analysis.
  • Craig Norris, CEO at Attensity, similarly famed three varieties of challenge, in his case relating to technology, implementation and seeing occasion in adverse traffic conditions:

  • Getting sentiment right: Many of the vendors in the text-analytics space fill pretty suitable text classification technology – where the application classifies terms based on dictionary entries or predefined lists. The output looks suitable – but because only terms are looked at, there tend to subsist a lot of fake positives – negations are missed, relationships (such as why someone is unhappy) are never found. Many customers fill purchased technology that only goes this far. They will subsist challenged this year by consumers of the data who find the data is, in fact, wrong. Natural language processing (NLP) technology fancy Attensity's not only finds sentiment; it can find sentiment in context, determining accurately whether it's negative or positive, the degree [or intensity] of it, and the “why” behind it.
  • Getting to Action: Another challenge this year will subsist around getting past high-level views of the data (general ratings of sentiment, general views of issues) to the root cause so that users can select action and companies can regain real value. For example, knowing not only that a customer is unhappy with a product, but besides that they intend to recur it if they don't regain a summon back or a fix for their problem is faultfinding to being able to remedy a situation and reclaim a customer. Being able to know this is where the real ROI is for text analytics products. This is only workable with an approach that not only finds sentiment but can besides understand the relationships between the issues and the reasons for the issues.
  • The economy: Certainly the economy will subsist a challenge for any technology solution vendor this year. Their offering has proven to enable two things to encourage companies in a tight economy: revenue preservation – find out if customers are going leave, understand why and reclaim them; and revenue growth – understand if customers are having issues ("cries for help") and delight them by acting on those issues. This generates incredible word of mouth and ultimately growth.
  • Solutions Focus

    Vendor prognosticators with a solutions focus comprise Keith Collins, CTO at SAS, and Manya Mayes, SAS Chief Text Mining Strategist, remark as challenges for 2009:

  • A broader set of vertical/horizontal offerings including more automated unstructured (text, voice, image) capabilities must subsist delivered for customer/product/competitive intelligence. SAS is doing this, for example, with SAS Text Miner integration into SAS Warranty Analysis. Automated capabilities comprise graphics, sentiment analysis, net promoter scores, and key performance indicators (KPIs) from text analysis results.
  • Solutions providers must select text analytics and search across the breadth of their offerings: For SAS, text+DI [data integration], text+BI[business intelligence], text+DataFlux, text+JMP, text+SOO [Service Operations Optimization], etc. SAS customers are requesting these capabilities, and they are structure software and planning road maps accordingly.
  • Customers are consolidating software and needing to settle on one vendor that can ply whole approaches to text – text analytics/mining/business analytics/search/categorization.
  • Collaboration and mobile BI are faultfinding needs, and vendors necessity to subsist agile and accelerate technology swiftly to meet the needs of consumers.
  • Yves Schabes, President of Teragram, a SAS company, focuses his response on one particular challenge – increasing workers’ efficiency:

    Given the current economic situation, large organizations are forced to support up a speedily pace of traffic with fewer resources, and it is therefore faultfinding that these organizations fill whole of their content organized correctly so that employees can spend more time fulfilling their jobs and less time searching for information on their enterprise's system.

    Neil Hartley, CEO of Leximancer, sees “an industry that has been around for a long time and yet has seen minute in the way of being operationalized within traffic processes.” Neil continues:

    Yes, there are proofs of concept, elude by experienced vendor staff but these [prototypes], in my experience, rarely regain adopted by the traffic a) because of the setup and maintenance required, and b) because the source data vocabulary changes making the initial setup redundant. Autonomy is the exception, but their deployments are largely search/retrieval-based and less qualitative.

    What the traffic needs is a lofty degree of automation (without the necessity for extreme setup and maintenance) together with clarity in the analysis and the competence to apply control to the process where needed. This is exactly what Leximancer provides.

    The other major trend I remark is the necessity to accomplish social media actionable, and this is something we’ve focused on heavily on their blog. I judge customer attitudes on social media or microblogging sites are a leading indicator for the business. The traffic that waits for these trends to subsist reflected in their formal feedback programs may find it is too late to select effectual action.

    Technology and Applications

    I had expected that a higher balance of 2009 “challenges” responses would focus on the technology and its applications. Responses I’ve already quoted touch on those areas with perhaps greater attention to traffic and market concerns. Eric Martin, Product Marketing Manager at SPSS, focused solely on solutions, which to me reflects both Eric’s aplomb in his company’s market position and his own background: Eric earned a Ph.D. in immunology and cellular biology and, fancy many others, started using text mining on biomedical articles before joining text analytics pioneer LexiQuest, which was later acquired by SPSS. Challenge areas Eric sees for 2009 are:

  • Blog analysis: Already seared and will probably regain bigger in 2009. There's a lot of confusion though between blogs and other kindly of user-generated content or Web 2.0 data. That's besides very solution-oriented and not only requires text analytics but besides data mining, Web scraping capabilities, etc.
  • Sentiment analysis: Not an option anymore in most projects. fragment of Voice of the Customer, blog analysis applications, etc. lofty attribute out-of-the-box results are demanded more and more.
  • Automated translation: besides getting more and more market traction prior to text analysis.
  • Matthew Hurst of Microsoft Live Labs is likewise a techie at heart, and he’s besides very interested in user-generated and other online content. Matthew says, “As reported elsewhere in research and industry literature, the majority of textual data being published online today is from the many genres of social media. To fully leverage this data, the key challenges are:

  • Comprehensive and complete data acquisition: Due to the social nature of this content, missing documents or authors is fancy missing the replies to answers or key voices in the choir.
  • Tuning or recreating standard tools to deal with less formal content: Tokenization, sentence segmentation, part-of-speech (POS) tagging, parsing, etc. whole fill different qualities and requirements in the social space.
  • Development and upkeep of broad (product) ontologies: This is a key requirement for grounding any analytics.
  • Lastly, Ren Mohan, Co-Chairman and CTO of IxReveal, replied not only with the three challenges his company hears most often from their clients, but besides with a couple of “megatrends” he is genesis to see. Challenges are:

  • Speed to implementation: Clients remain concerned about implementation taking months before realizing any benefit. Immediate payback, more fancy a couple of weeks, seems to subsist the mantra!
  • Systems should dynamically and quickly react to changing modern information: Clearly, clients enact not want to depart through an extensive process of rebuilding their analysis when requirements for analysis change. whole their customers support changing their analysis as modern information unfolds.
  • Finding actionable intelligence in data that is not grammatical: Less time in summon handling, texting, minute patience, quick notes by data sources – this implies an increasing amount of text data has embedded meanings but is less grammatical. So, their clients are asking us to encourage them resolve such data as well.
  • Ren’s “megatrends” are:

  • The line between structured and unstructured is blurring and a modern trend is emerging: Users want a modern approach altogether. As opposed to converting unstructured to structured, users would fancy to remark it the other way, and they want it quickly and easily. In the ISO [insurance industry] fraud/claims management conference, the keynote presenter asked how many wished their systems could respond with Google-like access and ease; 100% of the audience raised their hands. When he asked how many of their systems behave fancy that today, no hands went up! They are whole using SQL. So, they remark a modern trend in analysis going from structured (SQL fancy complexity) to unstructured (search fancy simplicity)!
  • Thus far, text analytics has been available only for mega corporations! Now, the trend is catching on in the consumer/desktop user world as well. Products like uReka! from IxReveal and SearchWiki from Google are examples. They give users a way to store and reuse search queries and links, and personalize them. This is the genesis of analysis as users fill to now judge (analyze) about content databases, links, social networks, etc.
  • Ren’s conclusion: “These are truly exciting times!” Indeed.

    A Live Challenge?

    Here are thoughts on one more potential challenge for 2009, a live challenge, of a different variety.

    As an aside while forwarding his select on 2009 text-analytics challenges, Lexalytics’ Jeff Catlin suggested a bake-off to subsist held at the 2009 Text Analytics Summit, which is slated for June 1-2 (preceded by tutorials) in Boston. Jeff says in his blog, “Our market is still dominated by too much flashy marketing and not enough down in the dirt numbers for ‘apples to apples’ comparisons.” Jeff is right, although I’ll add that I believe that most of the flashy marketing actually fronts very capable products. Perhaps they can regain something going for this year – a commercially oriented version of the TREC (Text REtrieval Conference) challenge. Stay tuned, and enact deem attending this year’s summit.

    And if you’re a current or prospective text analytics user and would fancy to Tell me about challenges you pan or expect to face, please enact regain in touch by email at grimes@altaplana.com or by phone at (301) 270-0795).

  • Seth GrimesSeth Grimes

    Seth is a traffic intelligence and decision systems expert. He is founding chair of the Text Analytics Summit and principal consultant at Washington, D.C., based Alta Plana Corporation. Seth consults, writes, and speaks on information-systems strategy, data management and analysis systems, IT industry trends, and emerging analytical technologies. Seth chairs the Sentiment Analysis Symposium and the Text Analytics Summit.

    Editor’s Note: More articles and resources are available in Seth's BeyeNETWORK Expert Channel. subsist sure to visit today!

  • Recent articles by Seth Grimes


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    Parental tryst with Literacy Health Lens Analysis (HLA)

    Education

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    Aboriginal Road Safety- Drivers Licensing HLA

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    Minor augment in Aboriginal people with driver’s licences in remote communities, which is likely to reduce road accidents and incarceration rates

    Promoting International Students’ Health and Wellbeing HLA

    Education; Multicultural

    Resources for international students on health services access and maintaining well-being produced

    Healthy Sustainable Regional Communities in the Upper Spencer Gulf HLA

    Primary industries; Trade & economic development

    Awareness of weight of considering health and equity issues in regional planning increased in trade and economic portfolios and data atlas to support this

    Healthy Weight: A Desktop Analysis and Implementation Plan

    Health; Planning & infrastructure; Community services & welfare; Primary industries; Environment & natural resources; Education; Correctional Services; Justice

    Large reach of departments made alert of the impact they fill on population uninterested weight and the potential actions they can select to achieve the well weight target. Progress on strategies within departments reported to Parliament annually

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    Local government

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    Planning & infrastructure

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    Minimal impact but provided some rationale for considering health and wellbeing in migrant settlement

    Alternative Water Supplies – Water Security

    Environment & natural resources

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    Education

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    Premier and Minister for Education supported by DPC and Education sector

     

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    Premier, Treasurer supported by DPC and Finance

     

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    Premier, Minister for Industry & Trade supported by DPC and Trade & economic development

     

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    Recommendations for entertainment venues about how they can support well eating for families

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    Health, DPC, Office for the Public Sector, Environment & natural resources

    Lessons from the HiAP taste of cross sectoral working directly informed this initiative and underpinned the strategies developed as fragment of it

    Applying HiAP Principles to work with Public Health ally Authorities (PHPA) across SA

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    - Planning & infrastructure. Policy focus is on planning reform, urban renewal and well built environment

    - SA Council of Social Services. Policy focus is on the role of non-government sector in public health planning system

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    - Community services & welfare. Policy focus is on whole of government Wellbeing Framework concept and measurement; increasing access to well nutritious food for vulnerable people at risk of hunger.

    Relatively modern initiative (since 2015). The legislative basis of the PHPA vow to encourage health become more prominent in the activities of those agencies that sign up to subsist a PHPA



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