hermes: a semantic web-based news decision support system*

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March 17, 2008 SAC WT 2008 1 Hermes: a Semantic Web-Based News Decision Support System* Flavius Frasincar [email protected] Erasmus University Rotterdam * Joint work with Jethro Borsje and Leonard Levering

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Hermes: a Semantic Web-Based News Decision Support System*. Flavius Frasincar [email protected] Erasmus University Rotterdam. * Joint work with Jethro Borsje and Leonard Levering. Contents. Motivation Hermes Framework: News Classification Query Formulation Results Presentation - PowerPoint PPT Presentation

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Page 1: Hermes: a Semantic Web-Based News Decision Support System*

March 17, 2008

SAC WT 2008 1

Hermes: a Semantic Web-Based News Decision Support System*

Flavius [email protected]

Erasmus University Rotterdam

* Joint work with Jethro Borsje and Leonard Levering

Page 2: Hermes: a Semantic Web-Based News Decision Support System*

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SAC WT 2008 2

Contents

• Motivation

• Hermes Framework:1. News Classification

2. Query Formulation

3. Results Presentation

• Hermes News Portal:– An example

• Conclusions

• Future Work

Page 3: Hermes: a Semantic Web-Based News Decision Support System*

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Motivation

• Large quantity of news on the Web:– Difficult to find the ones of interest

• Limited annotation of RSS feeds:– Broad categories (business, cars, entertainment, etc.)

• News messages have a big impact on stock prices

• Google finance shows direct news which pertain to a certain portofolio:– Indirect news (competitors of Google like Microsoft are not

presented)– Not possible to ask (time-related) queries about news

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Hermes Framework

• Input: – News items from RSS feeds– Domain ontology linked to a semantic lexicon (e.g., WordNet)

• Output:– News items relevant for a particular user

• Three steps:– News Classification:

• Relate news items to ontology concepts

– Query Formulation• Allow the user to express his concepts of interest

– Results Presentation• Present the news items that match user’s concepts of interest

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1. News Classification

• Concept defined in the ontology (class or individual)

• Multiple lexical representations for the same concept:– Ontology synonyms (e.g., New York → New York, Big Apple)– Semantic lexicon synonyms (e.g., buy → acquire)

• Concepts without subclasses or instances:– Semantic lexicon hyponyms (e.g., company → dot-com)

• Lookup ontology concepts into news items

• Heuristics: at least three hits (concepts) in a news item

• Work in progress: use a word sense disambiguation algorithm (e.g., SSI, GAMBL)

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1. News Classification

• The news classification process:

Page 7: Hermes: a Semantic Web-Based News Decision Support System*

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2. Query Formulation

• Present the domain knowledge as directed labeled multi-graph:– with the additional constraint that arcs between two nodes are

not allowed to share the same label

• User selects the concepts of interest in the original graph (e.g., Google)

• User is able to add to its selection concepts related to the concepts of interests via a certain relation (e.g., hasCompetitors: Microsoft, eBay, and Yahoo)

• The selected concepts are presented in a separate graph (called search graph)

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2. Query Formulation

• News are time stamped

• User is able to specify that only news in a certain time interval should be retrieved

• Time constraints:– Last hour– Last day – Last year– [2007-03-01T00:00:00.000+00:01, 2007-05-

31T00:00:00.000+00:01 ]

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3. Results Presentation

• Return news items that match a query

• Present the concepts involved in the query

• Per each news items show a summary:– Title– Source– Date– Few lines from the news item

• Emphasize the hits (found concepts from the ontology) in the retrieved news items

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Hermes News Portal

• Hermes News Portal (HNP) is an implementation of the Hermes framework

• Implementation language: Java

• Ontology represention langauge: OWL

• Semantic lexicon: WordNet

• Graph visualization: Prefuse

• Query language: SPARQL

• SPARQL extended with custom time functions (e.g., currentDate(), currentTime(), etc.)

Page 11: Hermes: a Semantic Web-Based News Decision Support System*

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An Example

• Query:

Which are the news items interesting for Google from the past three months?

Page 12: Hermes: a Semantic Web-Based News Decision Support System*

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News Classification

• Conceptual graph:

Page 13: Hermes: a Semantic Web-Based News Decision Support System*

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2. Query Formulation

• Concepts selection:

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2. Query Formulation

Individuals

Classes

Selected concepts

Concepts relatedto the selected node

Concepts fromkeyword search

• Conceptual graph:

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2. Query Formulation

• Search graph:

Page 16: Hermes: a Semantic Web-Based News Decision Support System*

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2. Query Formulation

PREFIX hermes: <http://hermes-news.org/news.owl#>SELECT ?titleWHERE {

?news hermes:title ?title .?news hermes:time ?date .?news hermes:relation ?relation .?relation hermes:relatedTo hermes:Google .FILTER(

?date > "2007-03-01T00:00:00.000+00:01" &&?date < "2007-05-31T00:00:00.000+00:01"

)}

• SPARQL query:

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2. Query Formulation

• Custom time functions:

Function name Output typecurrentDate() xsd:date

currentTime xsd:time

now() xsd:dateTime

dateTime-add(xsd:dateTime A, xsd:duration B) xsd:dateTime

dateTime-substract(xsd:dateTime A, xsd:duration B) xsd:dateTime

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2. Query Formulation

PREFIX hermes: <http://hermes-news.org/news.owl#>SELECT ?titleWHERE {

?news hermes:title ?title .?news hermes:time ?date .?news hermes:relation ?relation .?relation hermes:relatedTo hermes:Google .FILTER( ?date > hermes:dateTime-substract(hermes:now(), P0Y3M) &&

?date < hermes:now())

}

• Extended SPARQL query:

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3. Results Presentation

Page 20: Hermes: a Semantic Web-Based News Decision Support System*

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Conclusions

• Hermes Framework: presents news items that match the user interests

• Hermes Framework:– News Classification– Query Formulation– Results Presentation

• Hermes News Portal (HNP): an implementation of the Hera framework

• HNP based on:– WordNet semantic lexicon, OWL ontology, (extended) SPARQL

queries, Prefuse visualization

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Future Work

• Word Sense Disambiguation:– SSI– GAMBL

• Ontology updates:– Learning from news items– Check if the extracted information obeys the ontology axioms:

• Faulty extraction• Ontology axioms update

• Simplify the query interface:– Allow users to ask English queries from a limited vocabulary

• Evaluate the tool outside the university lab