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Research Interests

Pierre Senellart

Ranked XML Querying Dagstuhl Seminar

10 March 2008

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 1 / 4

(2)

Understanding the Hidden Web

WWW

HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User discovery

discovery probing

wrapper induction semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(3)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages

Web service

Analyzed

Web service Service index

User

discovery

discovery

probing wrapper

induction semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(4)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User

discovery

discovery probing

wrapper induction semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(5)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User

discovery

discovery probing

wrapper induction

semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(6)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User

discovery

discovery probing

wrapper induction

semantic analysis

indexing

query results

Problem Studied (with people at INRIA Lille)

Using a preliminary imperfect and imprecise annotation by domain knowledge for bootstrapping astructuralwrapper induction.

More on this on Thursday !

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(7)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed Web service

Service index

User

discovery

discovery probing

wrapper induction semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(8)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed Web service

Service index

User

discovery

discovery probing

wrapper induction semantic analysis

indexing

query results

Problem Studied (with Georg Gottlob, University of Oxford) Deriving from two database instances of distinct, unknown, schemata anoptimalmapping. Based solely on the occur- rences of constants in the two instances.

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(9)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User

discovery

discovery probing

wrapper induction semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(10)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User discovery

discovery probing

wrapper induction semantic analysis

indexing

query results

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(11)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User discovery

discovery probing

wrapper induction semantic analysis

indexing

query results Problem Studied (with Serge Abiteboul, INRIA Saclay)

Services of the hidden Web described by Datalog-like rules.

Answering queries usingviewswith binding patterns(LAV setting). Work very much in progress.

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(12)

Understanding the Hidden Web

WWW HTML form

Analyzed form + result pages Web service

Analyzed

Web service Service index

User discovery

discovery probing

wrapper induction semantic analysis

indexing

query results Problem Studied (with Serge Abiteboul, INRIA Saclay)

A model for storing, querying and especiallyupdating pro- babilistinginformation inXML, in the spirit of conditional tables in the relational context.

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 2 / 4

(13)

The Web as a Graph

Related Nodes in a Graph (with Yann Ollivier, ENS Lyon)

Using Green measures to define a semantic neighborhood of nodes in a graph, e.g., for extracting related pages.

PageRank Prediction (with Michalis Vazirgiannis, Athens Univ. of Economics & Business)

Prediction of the

evolution of PageRank

using hidden Markov models to decrease the needed crawl refreshment rate.

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 3 / 4

(14)

The Web as a Graph

Related Nodes in a Graph (with Yann Ollivier, ENS Lyon)

Using Green measures to define a semantic neighborhood of nodes in a graph, e.g., for extracting related pages.

PageRank Prediction (with Michalis Vazirgiannis, Athens Univ. of Economics & Business)

Prediction of the evolution of PageRank using hidden Markov models to decrease the needed crawl refreshment rate.

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 3 / 4

(15)

(Very) Preliminary Research Interests

Data Corraboration (with Amélie Marian, Rutgers, and Serge Abiteboul, INRIA Saclay)

How to use the redundancy of facts stated by different sources (e.g., on the Web) to estimate the confidence in these facts ?

Automatic Extraction of Relations Between Entities From Text (with people at MPI-Informatik)

How to extract (a priori unknown)

relations

between known entities from a

textual corpus

referring to these entities ?

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 4 / 4

(16)

(Very) Preliminary Research Interests

Data Corraboration (with Amélie Marian, Rutgers, and Serge Abiteboul, INRIA Saclay)

How to use the redundancy of facts stated by different sources (e.g., on the Web) to estimate the confidence in these facts ?

Automatic Extraction of Relations Between Entities From Text (with people at MPI-Informatik)

How to extract (a priori unknown) relations between known entities from a textual corpus referring to these entities ?

P. Senellart (MPII & U. Paris-Sud) Research Interests Dagstuhl, 2009/03/10 4 / 4

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