a formal model to the routing questions problem
DESCRIPTION
Apresentação no ICWI 2011TRANSCRIPT
A formal model to the routing questions problem in the context of
Cleyton Caetano de Souza
Schedule
1. Introduction
1. Problem
2. Related Works
3. The model
1. The problem
2. Details
4. A solution to the model
5. Conclusion
6. Future Works Cleyton-UFCG 2
Introduction
β’ Web has became essential
β Web, a repository of information
β’ Search Engines
β Looking answers
β’ Social Networks
β Waiting answers
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Problem
β’ Could occurs problems when you publish your question
β None answer
β None see
β Many answers
β’ Direct the answer to someone
β You ensure a answer, but will be a good one?
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Problem
β’ Informally, the problem that we proposes to solve is given a question posted by a user (asker) in Twitter, find among his followers that user with the characteristics:
β (1) knows the answer
β (2) has the trust of the questioner
β (3) provide the answer quickly
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Related Works
β’ (Morris, Teevan e Panovich 2010a)
β 93.5% of users received answers to their question after post them and these responses
β in 90.1% of cases, were provided within one day
β’ Applications
β Aardvark (Horowitz and Kamvar 2010)
β Q-Sabe (Andrade et al 2003)
β’ The differential of our research
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The Model
β’ The twitter is defined by the tuple
π = {π, π }
β’ Where π = {π’1, β¦ , π’ π } is a set of users
β’ And π is the set of all relationships ππ,π between two users π and π.
β The existence of ππ,π means that i follows j, this
way ππ,π β ππ,π
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The Model
β’ Each useru has the attributes
β πΉπππππ€πππ π’ that contains all users which follows π’
β πΉπππππ€ππππ’ that contains all users which are followed by π’
β ππ’ = π1, β¦ ,π π a ordered list that contains all
messages posted for π’
β’ Each message π has the attributes
β ππ- the post date
β π π- the string posted
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The Problem
Given a query π posted by π’,
π β πΉπππππ€πππ π’ and ππ,π a function
that tell us the chances of
π provides a good answer
β Find: π
β To: πππ₯ ππ,π
β Over: πΉπππππ€πππ π’
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The problem
β’ We believe that ππ,π has a correlation with
three things
β ππ,π β the knowledge that π in relation with π
β π‘π’,π β the trust of π’ has in π
β ππ β the level of activity of π
β’ That way will actually want to find the best combination of: ππ,π, π‘π’,π and ππ
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Knowledge
β’ Each message ππ’ corresponds a fraction of the total expertise of π’
ππ’ = πππ’ππ’βππ’
β’ In IR we represent this fraction as a vector of the words/token contained in ππ’
β’ So the ππ’ is a vector where each coordinate represents a token and its value is the frequency of this token in all messages ππ’
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Knowledge
β’ If π‘π is the frequency of the token π‘ in π, the
knowledge needed to answer satisfactorily the question is calculated as a inner product between the vector that represent the follower and the vector that represent the question
ππ,π = π‘π β π‘ππ’π‘βπ
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Trust
β’ Trust is related to
β Friendship [Schenkel et al 2008]
β Similarity [Kuter and Golbeck 2010]
β’ So we believe (and simplify) π‘π’,π£ = ππ’,π£ β π ππ π’, π£
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Friendship
β’ Friendship measures the importance of a user to another
β’ In Twitter a good estimative of friendship should consider the mentions (connections) between π’ and π£, so
ππ’,π£ =|ππππ‘ππππ π’ π£ |
ππππ‘ππππ π’
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Similarity
β’ The similarity measures how to users are equal under some criterion
β’ Appears intuitively that the similarity is related to equality among the attributes
π ππ1 π’, π£ βπΉπππππ€πππ π’ β© πΉπππππ€πππ π£πΉπππππ€πππ π’ βͺ πΉπππππ€πππ π£
π ππ2 π’, π£ βπΉπππππ€ππππ’ β© πΉπππππ€ππππ£πΉπππππ€ππππ’ βͺ πΉπππππ€ππππ£
π ππ3 π’, π£ β π ππ(ππ’, ππ£)
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Similarity
β’ Any combination of this equations could be used
β’ We choose use
π ππ π’, π£ =π ππ1 π’, π£
1 β π ππ1 π’, π£βπ ππ2 π’, π£
1 β π ππ2 π’, π£βπ ππ3 π’, π£
1 β π ππ3 π’, π£
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Activity
β’ Users not interact with the same intensity
β’ It seems intuitive that the activity level of a user depends on the frequency with he/she post new tweets
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Activity
β’ Activity means the mean time between the messages posted by π’
ππ’ =π‘ππππ¦ β ππ, ππ’ + ππ,π+1 β ππ,π
|π|π=1
ππ’ + 1
β’ As lower this value, most active is the user and bigger the chances of him give a answer quickly
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Solving the Model
β’ Calculate the tuples (ππ,π , π‘π’,π, ππ) to each
user is a simple task
β’ But, how decides who is the best?
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Solving the Model
β’ We consider this is a problem of decision making with multiple criteria
β’ We decide to use the Weight Product Model to solve based on [Triantaphyllou and Mann 1989]
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Solving the Model-Step 1
β’ The resolution of the model starts calculating the tuple (ππ,π , π‘π’,π, ππ) to each user
ππ’ β πΉπππππ€πππ π’
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Solving the Model-Step 2
β’ The we display this users in a matrix πΉπππππ€πππ π’ π₯|πΉπππππ€πππ π’|
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Solving the Model-Step 3
β’ We create a function πππ π₯ which will map the values of (ππ,π , π‘π’,π, ππ) in a same scale
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Solving the Model-Step 4
β’ For each pair π1, π2 |π1 β π2we calculate
ππ1,π2 =ππ1,π
ππ2,π
π₯
βπ‘π’,π1π‘π’,π2
π¦
*ππ1ππ2
π§
β’ The values π₯,π¦ and π§ are factors of importance and must be between 0 and 1, besides that π₯ + π¦ + π§ = 1
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Solving the Model-Step 5
β’ If ππ1,π2 > 0 we put 1 in position (π1, π2) and 0
in position (π2, π1)
β’ If ππ1,π2 < 0 we put 0 in position (π1, π2) and 1
in position (π2, π1)
β’ If ππ1,π2 = 0 we put 1 in position (π1, π2) and 1
in position (π2, π1)
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Solving the Model-Step 5
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Solving the Model-Step 6 (End)
β’ We calculate the sum of each line of the matrix, this number represents the number of victories of each user
β’ In the end we have
β’ The question will be
routed to the user
with more victories
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Conclusion
β’ The differential of our research
β We focus in a successful network
β We treat the problem over a new perspective
β We lead with a recent and interesting problem
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Future Works
β’ The model was already implemented
β’ We are investigating if our heuristics are coherent
β’ We will investigating
β If the indications of the model are accurate
β If direct questions is more effective
β What factor of importance is most important
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Thank You
β’ Any Question?
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