Information
- Publication Type: Student Project
- Workgroup(s)/Project(s):
- Date: 2017
- Date (Start): August 2017
- Date (End): October 2017
- Matrikelnummer: 1126483
- First Supervisor: Manuela Waldner
Abstract
The general functions of current web search engines are well established. A box is provided in which to type the queries and the engine returns a result list which users can evaluate. The autocomplete suggestions assist users in defining their problems, however there is a lack of support for an iterative manual refinement of the query. This additional aid can be beneficial when users not know the exact terms to describe the concept they are looking for. Therefore, the goal of this project is to show searchers how a slight variation of the query changes the results. With this information, they then can perform a targeted refinement of the query to access useful information sources. To achieve this goal, each part of the searcher’s query is varied with a thesaurus that provides synonyms for the individual query terms. While performing the user’s original query in a normal fashion, variations of this query are conducted in the background. To provide a concise visual summary of the query results, text mining techniques are performed on all gathered results to retrieve the most important key terms for each query variation. This procedure results in a visual overview of what the searcher’s query finds together with what could be found with a slight variation of the query. Additional queries should make users aware that alternative queries may be more appropriate when their original query is poorly formulated. In conjunction with some interaction tools, the goal is to reduce the burden of refining search queries and therefore making searching the web less complex.Additional Files and Images
Weblinks
No further information available.BibTeX
@studentproject{mazurek-2017-vows,
title = "Visualization of Thesaurus-Based Web Search",
author = "Michael Mazurek",
year = "2017",
abstract = "The general functions of current web search engines are well
established. A box is provided in which to type the queries
and the engine returns a result list which users can
evaluate. The autocomplete suggestions assist users in
defining their problems, however there is a lack of support
for an iterative manual refinement of the query. This
additional aid can be beneficial when users not know the
exact terms to describe the concept they are looking for.
Therefore, the goal of this project is to show searchers how
a slight variation of the query changes the results. With
this information, they then can perform a targeted
refinement of the query to access useful information
sources. To achieve this goal, each part of the searcher’s
query is varied with a thesaurus that provides synonyms for
the individual query terms. While performing the user’s
original query in a normal fashion, variations of this query
are conducted in the background. To provide a concise visual
summary of the query results, text mining techniques are
performed on all gathered results to retrieve the most
important key terms for each query variation. This procedure
results in a visual overview of what the searcher’s query
finds together with what could be found with a slight
variation of the query. Additional queries should make users
aware that alternative queries may be more appropriate when
their original query is poorly formulated. In conjunction
with some interaction tools, the goal is to reduce the
burden of refining search queries and therefore making
searching the web less complex.",
URL = "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/",
}