Cognitive Systems -Redefining the Library User Interface

Authors:

Kshama Parikh, Institute of Law Library, Nirma University. (kshamaparikh@nirmauni.ac.in)

Saurin Parikh , Florida Atlantic University, USA and Institute of Technology, Nirma University, India. (sparikh2014@fau.edu)

Dr. Hari Kalva, Florida Atlantic University, USA. (hari.kalva@fau.edu)

Dr. David Jaramillo, IBM, USA. (djaramil@us.ibm.com)

Problem – An Overview

• Library members may feel overwhelmed withinformation available on websites or library portalsand often requires human assistance to findpointers to needed information.

• In a eLibrary scenario, library staff cannot respondto members’ queries, 24/7 in real time.

• Ability to address to members concerns in real timemay lead to better service.

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Proposed Solution

• A cognitive system with an ability to interact,understand, reason, and learn just like a HumanBrain.• Interacts in Natural language, which may provide a feel of

having conversation with a library staff.

• Understand the context from the content just like a humanbrain.

• Does reasoning to provide confidence weighted responseswith supporting evidence.

• Learns and trains from new discovery and inputs, whichmay improve the responses.

• Cognitive system may reduce the effort and timeneeded to access resources and information.

Interact and

Learn

Reason

Understand

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Watson – The Cognitive System Platform

Watson a cognitive technology platform launched by IBM has an ability tounderstand, reason , learn and interact just like a Human. [1],[2]

Characteristics :

• Interact :- Watson, can engage in interaction with human users in naturallanguage by using chatbots.

• Understand :– can analyse unstructured and structured multimedia datasuch as text, images, audio, and video in order to predict context fromcontent.

• Reason :- has human like reasoning ability. It can identify user’spersonality, tone and emotional traits in order to provide personalizedrecommendations.

• Learn :- new discovered information. uses machine learning techniquesto train itself by learning from

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Why not just use a search engine /tool ?

Search Engine Scenario :

• In Google, if you type the query:

'anything that's not an elephant.'

• What do we get?

Many images related to elephants.

Watson Scenario :

• It understands the context from the contentand does not retrieve information only onbasis of ngram matches from the query.

• It understands that difference betweenfollowing phrases, as both have totallydifferent context [2]:

"when feet run" and "when noses run", 5

How Does Watson Work ? (A comparison with conventional computing approaches)

Conventional Computing approaches Cognitive Systems (Watson’s Approach)

Handles structured dataExample: Data stored in the databases.

Along with Structured Data, it also understands,unstructured data that occupies huge amount of dataspace [1], [2]Example : reports, blogs, posts and tweets etc.

In order to respond to a Query it relies on wellspecified information of well defined fields ofstructured data stored in Database.

In order to respond to queries, it relies on naturallanguage, which is governed by rules of grammar,context, and culture [1], [2](Unstructured data is normally in natural language)

Query based Information Search is governed bykeyword matching (ngram matching).

Sentence is interpreted grammatically, relationally andstructurally. It understands context and predicts thereal intent of the users’ query [1][2].

Can not gain insight into domain specific knowledgeover time.

Watson works in a particular field or Domain, itlearns the language, the jargon and gains domaininsight and knowledge from experiences [1],[2],[3]6

How Does Cognitive System (Watson) collect Domain Knowledge – An Overview

Watson Cognitive

System

Loads the relevant body of literature

Content is curated

(Selected & organized)

Undergoes data

ingestion (importing Data into Database)

Create a knowledge

graph

Learns by using

machine learning approach

Training by human

experts and learning by

ongoing user interaction Cognitive Systems learns,

adapts and keeps relearning Domain Knowledge.

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IBM Watson – Available as set of Services

• Watson is available as set of services and service can be integrated [1],[5]. Watson Services [4][5] :

Higher Reasoning Skills• Conversation• Language Translation

Knowledge OrganizationSkills• Document Conversion• Retrieve & Rank• AlchemyLanguage• AlchemyData News

Foundational CognitiveSkills• Speech to Text / Text to Speech• Personality Insights• AlchemyVision / Visual Insights• Visual Recognition 8

Architecture of a Cognitive System

Interfaces

Library System

Watson Cognitive

System (Library

Assistant)

Conversation Service

Other Services

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Library User Robots

Messenger

IOT Apps

Mobile Apps

Non SQL Data sources (Unstructured Data)

SQL Database

Watson Characteristics – Interacting like a Human – Introduction to Conversation Service

What is Conversation Service and its uses?

• Conversation service allows to create virtual agents and bots that combinemachine learning, natural language understanding, and integrated dialog toolsto provide automated customer engagements.

• Natural language interface can be added to applications in order to Automate interactions with end users. (Human like conversation) and allows to build natural conversation flows between apps and users.

• Can integrate chat bots into web / mobile application which can communicate on any channel or device.

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Basic Conversation Service Pattern (How it works)?

• Heterogeneous Input Platforms: Watson conversation service adds conversational capability to apps such that it can interact with end-users on their platforms of choice, such as :Mobile apps , messaging, IOT and robots.

• Natural Language Classifier andthe conversation service-buildingBlocks : allows to input our librarydomain expertise in form ofIntents, Entities and Dialogs

• Watson Dialog Implementation :The service outputs a trainedmodel, which will enableconversation in natural languagewith end users.

Intents

Entities

Dialogs

Intent Example : Search a resource

Source : The Era of Cognitive Computing (by Rob High, Jr, IBM)

Entity Example : Sodhaganga

Trained Model

1) User Input Examples: Context : eLibrary accessa) cant find Sodhaganga b) Where is link of Sodhaganga?c) I need to refer to Sodhaganga

2) NLC Classifier (Prediction)Intent predicted : Search a resource.Confidence Weightage : 0.89123Entity predicted : online resource Confidence Weightage : 0.953213) Provide Response : invokes the database system or retrieves related web links for providing to user

Natural Language Classifier

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What are Intents ?

• An intent is the goal or purpose of the user's input [3].

• Intent Examples : Possible interaction scenarios in a library• Member is searching for specific resource,

• Member inquires regarding accessibility of resources from off campus,

• Need to know transaction rules for issue, renew ,reserve or return a resource,

• Searching for the location of the resource,

• Inquire about resource availability,

• requires alternate recommendation on non availability of a resource,

• Specific questions about membership rules,

• Needs resource recommendation, pertaining to a concept.

• User conversation examples are added to intents in order to help our chat-botunderstand different ways in which people would interact with it (All possibleexamples are not needed to be added as it uses machine learning techniques topredict the intent)

• Examples on next slide12

Sample Library Intents, designed in IBM Watson [1]-[3].

IntentsUser Interaction examples

User Interaction examples

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What are Entities ?

• Entity is a portion of the user's input that can be used to provide a different responseto a particular intent [2][3].

• Values and synonyms of entities can be added and it helps bot learn and understandimportant details about users' intent [2][3].

• Following are few samples of library entities with their synonyms created in IBMWatson [1]-[3].

Entity :Resource Lending with its sample values and synonyms

Entity :Digital Resources with its

sample valuesEntity : Transaction-types with its

sample values

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What are Dialogs?

• It can define Conversation flows[2][3].

• Dialog uses intents, entities, and context from application to define a response to each user's input [2][3].

• Dialog defines how your botwill respond to user queries

• An example of Watson Dialog isshown on the right side on thisslide prepared using IBMWatson [1],[2][3][4].

Intent

Entity

Dialog (conversation flow) is designed for “searching a resource” intent

Watson Dialog – Library user dialog, a sample example

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Screen shot showing Natural Language Interaction Scenario – A sample example

One Conversation scenario for

searching and lending a resource

Click for

Demo

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Predicted Intent : #search-for-resource

Predicted Entity: @Resource-lending:Book

Dialog design: conversation flow

for searching a resource (intent : search resource-

lending

User Query : “do you have a book on Watson”

Cognitive System supporting various forms of expression (inputs)

Cognitive systems support various forms of expressions that are more natural for human interaction [5].

• Human expression (inputs) comes in many forms such as: Written, Verbal and Visual

How to learn various representation of Data in order to predict context, user intent and entities from user input ?

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Watson Uses Machine Learning Techniques with Deep Learning to learn representations of Data.

Watson uses Machine Learning Techniques with Deep Learning [5]

• Learns representations of data by modelling high-level abstractions and uses model architectures with multiple layers of non-linear transforms.

• Overcomes challenges of designing hand-crafted features for tasks [5]

“Pi Notation” (Product notation)

User Query : Show me books explaining this concept

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Summary

• Watson redefines the means of user interaction with library systemsby providing a more human like conversation in natural language.

• Watson simplifies the way of inputting domain expertise bydesigning intents, entities and dialogs.

• Library Cognitive system will learn the user behaviour and adapt totheir changing needs with help of machine learning techniques andformal & informal training.

• In few years. Cognitive systems will be replacing the role oftransaction processing systems[5].

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References

1) IBM Bluemix documentation, http://www.ibm.com/bluemix.

2) Learn how IBM Watson works and has similar thought processes to a human, http//www.ibm.com/Watson.

3) ZeroToCognitive, https://www.youtube.com/watch?v=Jj7IFjd3FyI&index=1&list=PLnJzIOiv6cVTaS8k90R3T9AlS_kf5XWmX

4) https://github.com/rddill-IBM/ZeroToCognitive

5) Era of cognitive computing-Technical Strategy, Rob High Jr, IBM

Thank you

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