model driven crowdsourcing of search (crowdsearch2012 workshop at )
DESCRIPTION
Even though search systems are very efficient in retrieving world-wide information, they can not capture some peculiar aspects and features of user needs, such as subjective opinions and recommendations, or information that require local or domain specific expertise. In this kind of scenario, the human opinion provided by an expert or knowledgeable user can be more useful than any factual information retrieved by a search engine. In this paper we propose a model-driven approach for the specification of crowd-search tasks, i.e. activities where real people – in real time – take part to the generalized search process that involve search engines. In particular we define two models: the“Query Task Model”, representing the meta- model of the query that is submitted to the crowd and the associated answers; and the “User Interaction Model”, which shows how the user can interact with the query model to fulfill her needs. Our solution allows for a top-down design approach, from the crowd-search task design, down to the crowd answering system design. Our approach also grants automatic code generation thus leading to quick prototyping of search applications based on human responses collected over social networking or crowdsourcing platforms.TRANSCRIPT
A Model-Driven Approach for Crowdsourcing Search
CrowdSearch 2012 workshop @ World Wide Web Conference (WWW2012), Lyon, April 17th, 2012
Alessandro Bozzon, Marco Brambilla, Andrea MauriPolitecnico di Milano
Contact
Outline
• Rationale
• (Meta)Models
• Application
• Demo
• Outlook
SW Models + Social + Search =
MD CrowdSearch
• From exploratory search to friends and experts feedback
• Emphasis on social relations more than anonymous crowds
Rationale: increasing quality in exploratory search
Exploratory Search System
Human Search System
Initial query
Exploration step
Exploration step
System API Social API
Database / IR index
Crowd / Community
Example
• Multiple social platform deployment
Deployment: Advantages of MDD
Embedded application
Social/ Crowd platformNative
behaviours
External application
Standalone application
API
Embedding
Community / Crowd
Generated query template
Task splitting: the collection is too complex relative to the cognitive capabilities of users.
Task structuring: the task is too complex or too critical to be executed in one shot.
Task routing: a task can be distributed according to the values of some attribute of the collection.
User interaction: search tasks may imply complex UI design
• Easy to address through a model-driven approach
Search task management problems
Apply model-driven techniques to Social and Search:
Efficient development of CrowdSearch apps
MacroTask Description (BPMN)
User Interaction Model (WebML+ER)
M2M Transformation
M2T Transformations
Stand-alone application
Application embedded in social network
MicroTask Description (BPMN)
M2M Transformation
Social Process Model
It is used to define:•Social actors (e.g., Community Pools)•Social Activities (twittering, voting, following..)•Social events
Based on BPMN social design patterns
Social Application Model
It is used to define:•Exchange of user profiles from/to SN•Social data (e.g., shared content)•Interface and components for social tasks (e.g., twittering, voting, tagging, following)
Based on WebML social components
Process and applications models are extended to (task- or incorporate social issues: login, post, tag, rate, share, ... Platform- specific)
Model extensions for Social BPM
Vote
Comment
The content (meta)model
Field
type: String
name: String
Schema
name: String
FieldInstance
value: String
Query
question: String
type: String
open: boolean
User
user: String
password: String
email: String
Asker
Relation
type: String
CrowdObject
OutputInput
N 1
N 1
Outgoing From
Incoming To
Answer
1 N
1 1
idField
N 1
1
N
1
1
1
1
1
N
N
N
NResponder
N
N
N
1
N
• Like• Add• Comment• Modify • …
• user interaction + integration with social platform
Model for defining a question:
WebML models – question definition UI model
WebML models – Response UI model
Rendering of the application (summary)
• WebRatio (www.webratio.com), MDD tool that manages app development in three steps:
Model Driven Engineering of SocialSearch applications
Designthe Model
Customizethe Rules
Generatethe Application
• MDD Tools enable: fast prototyping, multi-platform deployment, model-driven debugging, and early assessment of alternative strategies
• See you on Friday, for the full paper presentation:
Answering Search Queries with CrowdSearcher Alessandro Bozzon, Marco Brambilla, Stefano Ceri
Social experiments and quantitative evaluations
Contact:Marco Brambilla
References
• www.searchcomputing.org
•www.bpm4people.org
• www.cubrikproject.eu
•www.webratio.com
Thanks!
Questions?