personalized interaction with semantic information portals eric schwarzkopf dfki...
TRANSCRIPT
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Motivation & Goals (1)
Literature research consists not only of information retrieval, but includes also
● Making sense of retrieved information● Locally organizing this information● Sharing gained knowledge
But existing portals focus on the IR process.
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Motivation & Goals (2)
● Support additional research activities● Identify and utilize relationships between
interactions to assist the user
– What are the relationships between sensemaking and information management?
– How can those be used to assist in information retrieval?
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Interaction Scenario (1 / 3)
Document Collection
1. build
s up
Working Context
2. uses
Information Portal3.1 expresses recommendation need
3.2 evaluates
User ModelRecommendations
3.3 updates3.4 ge
nerat
es
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Interaction Scenario (2 / 3)
1. browses
Information Portal
User Model
Recommendations
3.2 updates
Interaction History
2. implicitely creates 3.1 evaluates
Current Location
3.3 adds recommendations4. evaluates options
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Interaction Scenario (3 / 3)
1. identifies relevant items
2. adds items
Current Location
3. annotates items
Document Collection
Semantic Relationships
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Conceptual Overview
Information Portal
Document Manager
Recommender
Client
Server
•Browsing•Searching
•Organizing•Sensemaking
•Expressing user'sknowledge and needs
•Requestingrecommendations
•Utilizing IR-functionality
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Document Manager: Requirements
What are the main features a document manager has to provide?
– Possibility to spatially organize documents.
– Easy creation of informal structures.
– Creation of hierarchical structures.
– Annotation of documents.
– Possibility to define and browse semantic relationships.
– Searching the document collection.
– Sharing of created structures.
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Document Manager: WhiteboardCentral interaction component: A 2d whiteboard.
– Allows spatial organization of documents.
– Facilitates creation of informal structures and hierarchies.
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Document Manager: AnnotationsDocuments can be associated with free-form text annotations...
– Intended for pointing out relevant information contained in the document.
...and short descriptions displayed on the whiteboard.
– Intended as brief reminders.
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Document Manager: Semantic Relationships (1 / 5)
What about relationships between documents?
– “X contains a nice example of the material presented in Y.”
– “X improves on Y.”
– ...
Spatial organization and group hierarchies are not appropriate...
– Clutters the whiteboard.
– Not possible to express detailed semantics.
– Only facilitates the definition of symmetric relationships.
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Document Manager: Semantic Relationships (2 / 5)
...nor are notes or short descriptions.
– Cumbersome to define and utilize relationships.
– Relationships are hidden from the system, so it cannot use them to provide any assistance to the user.
Our approach:
– Provide an explicit, internal representation of semantic relationships.
– Allow the user to easily create and modify this representation via the whiteboard.
– Facilitate browsing this semantic network.
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Document Manager: Semantic Relationships (3 / 5)
Definition of relationships via drag and drop.
Browsing via a graph-based interface.
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Document Manager: Semantic Relationships (4 / 5)
User creates a semantic structure on top of the set of documents and the associated general metadata.
● Semantic relationships
– Content-based relationships
– Problem-specific relationships
● General metadata
– Bibliographic data
– Taxonomic relationships
● Document set
– unstructured
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Document Manager: Semantic Relationships (5 / 5)
Further applications of the semantic network:
– Query Augmentation● Identify documents related to the user's current query.● Use IR query augmentation techniques on this set of documents.
– User Modeling● Characterize current working context.● Assess interests and knowledge.
– Recommender● Provide relationship-specific recommendations.● “The work described in this document improves on the work presented in the
document you are currently reading.”
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Document Manager: Searching & Sharing
Support for text search.
– Full contents of documents.
– Notes associated with documents.
– Bibliographic data.
Collaborative support limited to sharing whiteboards.
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Recommender
Will provide content and strategic recommendations:
● Suggest papers likely of interest
● Recommend concepts to browse or limit a query to
– Names of authors
– Topic areas
– Conferences
● Provide hints for specializing or generalizing queries
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Recommender: Components
Recommender
Document Repository
Information Sources:● Knowledge Base● Semantic Networks● ...
Strategies
How to use info sources given a recommendation need.
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Recommender: Semantic Networks
Example Query: What documents use material presented in a given document?
Partial Net Partial Net Partial Net
Global, Weighted Network
Combine nets created by the user community.
Weight edges accordingto confidence.
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User Model
The UM represents:
● The user's knowledge and interests.
● The user's current working context.
● The user's current goal.
UM requirements:
● Intelligible.
● Accurate.
● Quickly adaptable.
● Comparable, mappable to KB and document space, ...
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User Model: Conception
Proposed conceptual model consists of three layers:
– General, fairly accurate, slowly adapting long-term profile.● Represents general interests in terms of ontological concepts.
– More specific, medium-term profile.● Represents the current working context (ontological concepts, characteristic
terms).
– Very specific, quickly adapting, but likely less accurate short-term profile.
● Represents the user's current information need (ontological concepts, characteristic terms).
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User Model: Data Sources
General Knowledge
Working Context
Current Information NeedInteraction withInformation Portal
● Recently accessed pages● Recent queries
Interaction withDocument Manager
● Recently accessed documents● Recent modifications of the KB
Personal KB
● Contained items● Structure
UM Layers
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User Model: Usage
UM
Data Functions
Query Augmentation
Result Filtering
Recommendations
Contains sets of weighted documents + metadata