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Question Answering in the Business Environment Yael Ravin T. J. Watson Research Center, IBM.

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Presentation on theme: "Question Answering in the Business Environment Yael Ravin T. J. Watson Research Center, IBM."— Presentation transcript:

1 Question Answering in the Business Environment Yael Ravin ravin@us.ibm.com T. J. Watson Research Center, IBM

2 Knowledge Management "Know what you know/don't know" Involving both people and IT –knowledge sharing culture (communities) –tools to enable access, processing, authoring and dissemination Inside and outside the enterprise –B2E - increase productivity; training; support innovation –B2C - online shopping; online support Within and across industries –B2B - dynamic marketplaces.

3 KM is a big market IDC & Knowledge Management Magazine survey (01/01): about 30% of IT budgets was allocated for KM in 2001 IDC WW KM Market forecast:

4 KM Challenges Improve support for information seeking –search, question answering, dialog systems –classification and visualization Identify useful information –recommendation systems, link analysis, personal profiles Reduce information overload –filtering, summarization Develop new ways to capture knowledge –phone, meetings, presentations

5 Portals: a KM path to market

6 A Simplified ‘one stop shopping’ Access to tools and information

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8 Lotus Knowledge Discovery System

9 NLP/IR Technologies in Portals today Search engine Document classification Document clustering Summarization Information Extraction Quality metrics Subscription and notification based on profile

10 Integrate QA in KM and portals Work within different business domains and needs: –shopping, expertise locator, business intelligence,... Integrate with other functionalities –a generic search engine –a dialog system Operate with multiple sources of information: –databases, text, presentations

11 Online Shopping Source: Forrester Report "Must Search Stink?" June 2000 Source: Meta Group Multiclient Enterprise Portal Study (1999)

12 Business Value: Search-Related Revenue Precision/Recall vs. "Find Rate“ Cycle: Enter Search -> learn -> shop -> buy -> receive -> use

13 Some ThinkPad Questions What hard disks can I add to my ThinkPad 570? How do I add memory to my ThinkPad? Can I buy an external monitor for my laptop? What docking station works with my ThinkPad 570? What's a port replicator? Can I buy a port replicator for my ThinkPad 570? What batteries are available for my ThinkPad? What power adapters are compatible with my ThinkPad 570? What keyboards are available for my ThinkPad? How do I add Ethernet capability to my ThinkPad?

14 Expertise Location Current system is "Person to Topic Affinity" - based on documents in the topic and the people who authored, contributed, distributed, read and subscribed Opportunity for Question Answering

15 Question Answering for Resumes Question Topics: –Education (degrees, certificates) programming languages, OS, applications, h/w, etc –Knowledge/expertise in a technical domain –Knowledge of industry experience w/ customers, or business analysis –Title/Role/Occupation e.g., analyst, engineer, sales rep –Previous customer engagements –Previous experience (including before IBM) –Geographic location and languages known

16 Sample Questions Who has professional experience with the Internet? Who has experience with Internet security? Who has participated in customer engagements involving Internet security? Who has led healthcare related engagements? Who is a systems architect in the sales and distribution industry? Who was project manager of an inventory management project? Who has a degree in AI and experience with expert systems?

17 Approach Search over metadata and structured data Handle joints –"systems analyst in publishing" Massage text: –multi-word NPs: Internet security, inventory management –missing subjects: "Developed Web apps..." –resume structure Domain ontology and knowledge of geography –"AI expert", "KM specialists in Europe" Extend semantic annotation for the domain –educational degrees, industries,...

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19 Conversational Interface for Shopping

20 Interaction

21 Conflict Resolution

22 Conversational Interface for Online Shopping Natural language dialog for finding IBM products on the Web Bridge the gap b/w consumer, business and content owner Based on NPs and keywords used by consumers to describe products Study compared w/ menu-driven app: –shortens interaction time by 33%, –reduces number of clicks by 63%

23 Virtual Assistant Address book –What is David's office number. –Create and new contact for Jim Hanks. Miscellaneous –This is John Doe and my passcode is 123456 –What time is it? –Hold on just a minute –Repeat that Messaging –Do I have any messages from John? –Fax that to 914-555-1234. –Send Jennifer a note. –Reply to that. –List the first 4 messages. –Delete the message from Rich. Calendaring –What's on my calendar next Tuesday? –Am I free tomorrow afternoon from 2 to 3? –Please set up a one hour meeting this Friday and invite Jane. –Delete today's meeting at 3 o'clock. Call management –Record a new voice greeting. –Hold all my calls until 1 pm. –Forward my calls to extension 5123. –Call Jim on his cell phone. –Conference Stella in on this call.

24 Virtual Assistant Intelligent speech understanding providing access to and control of business applications through broad class of devices. Unified messaging framework for e-mail, voice mail, and fax Create NL grammar by domain: e-mail, calendars, call management, general information

25 Issues for QA in business Integrate QA with other KM technologies Prototype QA for applications and learn what is useful Develop measures: –improvement attributable to QA –“good enough” for customers to use –cost of customization to new domains and applications


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