Using the Semantic Web for Web Searches Norman Piedade de Noronha, Mário J. Silva XLDB / LaSIGE, Faculdade de Ciências, Universidade de Lisboa.

Limitations in searching for information on the Web Lack of syntax: Information is stored in an unorganized manner. Lack of semantics: Machine processes do not understand the meaning of information. Unable to properly filter information for users which leads to information overload.

Semantic Web Searches Ex: Contacting an author of a certain article in a particular newspaper. Article´s Title  Article´s Author  Author’s Name  Author´s

Objectives 1. Build a SW search environment. 2. Evaluate & compare searches on this environment.

Hypothesis “Searches based on semantics improve user satisfaction and reduce effort by eliminating irrelevant results.”

Outline Motivation & The Semantic Web Motivation & The Semantic Web ReQuest for News & Validation ReQuest for News & Validation Conclusions & Future Work Conclusions & Future Work

ReQuest: Use Cases

Configure new domain in ReQuest 1. Selecting Input Data. 2. Configuring ReQuest. 3. Defining Equivalences. 4. Launching New Domain.

ReQuest for News

Validation Surveys with a group of 5 users. 9 queries on news domain. Measures on ReQuest and Google.

Examples of search queries (Q1) Find the post office address for the publisher Publico. (Q9) How many distinct articles were published by Publico about Futebol between the 5th of January, 2004 and the 7th of January, 2004.

Individual Query Survey How hard was the query to formulate? Did the semantic links help find the information? How long did it take to find the information? How relevant was the obtained information for your need? How many results were not interesting in the first page? Which search system was easier to use?

Global Survey Results Improve interface. Rank search results. Reduce information by providing a reduced version of results. Search within results. Search with properties from different contexts. Domain search preferred to Global search.

Hypothesis Validation “Searches based on semantics improve user satisfaction and reduce effort by eliminating irrelevant results.” Measurements: 1. Information Need Satisfaction. 2. Effort Reduction. 3. Irrelevant Results Reduction.

Measure 1: Information Need Satisfaction Only one user achieved greater success with Google. Google’s results better in only one out of nine queries.

Measure 2: Effort Reduction Majority of users were successfully aided by ReQuest approximately 7 times, while only 20% managed to solve more than half of the tests with less effort with Google. Some users did not produce a single test query where Google required less effort than ReQuest.

Measure 3: Irrelevant Results Reduction Only first page results were compared. 80% of users found fewer results with ReQuest than with Google. ReQuest was more precise than Google for 48.9% of all questions, while Google was more precise for 24.4%.

Conclusions Positive Feedback: Searches based on semantics improved user satisfaction and reduced effort by eliminating irrelevant results. Offering users the ability to select the search context is a more exact method for expressing the information need than key words. However, results not statistically significant for the universe of Web users or semantic assisted searches.

Future Work Domain searches enhanced with ability to restrict values. Multilingual Searches.

THANKS Thank you very much for your attention.