NUI Galway – UL Alliance First Annual ENGINEERING AND - ARAN ...

Abstract
The goal of this research is to create a search engine
that correctly ranks search results in terms of phonetic,
semantic and orthographic string similarity. Existing
and custom matching algorithms are combined and
then measured to find the greatest level of performance
and accuracy.
1. Introduction& Commercial Application
This project is being undertaken with contributions
from both NUI Galway and a privately owned
company, Enterprise Registry Solutions Ltd (ERS).
ERS are primarily involved with building electronic
registries for government agencies worldwide such as
the Companies Register Office in Ireland. One common
concern with company name registration is trying to
ensure similar names are not registered to operate in the
same jurisdiction.
A failure to enforce distinctiveness among registered
business names within the same jurisdiction can lead to
a number of problems: identity theft, complexity when
tracking cross border mergers or groups, and deliberate
misrepresentation in order to gain market share and
damage competitors.
With the growth of the EU it is common for
businesses to register and trade in multiple regions. In
response to this and to ensure transparency there have
been calls for a European wide Central Companies
Register [1]. The recent activity in this area highlights
the need for a scalable and accurate search engine. The
proposed system is labelled the Registered Organisation
Search Engine (ROSE).
2. String Searching Background
Fundamentally this project is an examination of the
performance of data retrieval methods within a specific
problem domain. The string similarity measures such as
Hamming Distance, Levenshtein Edit Distance and Jaro
Winkler all return similarity scores integral to the
ultimate ranking of results.
The hamming distance between two strings
can be computed by determining how many characters
must be substituted to transform one string to match the
other. Levenshtein Edit distances are similar but allow
addition, subtraction, substitution and transposition
between strings.
The Jaro Winkler Distance gives additional
weighting to terms with matching leading substrings.
The distance (dj) of two given strings s1 and s2can be
computed as follows
(
where m is the number of matching characters and t is
the number of transpositions.
String Matching In Large Data Sets
Liam Lynch & Colm O’Riordan
L.Lynch4@nuigalway.ie
)
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3. Problem & Approach
The ROSE system will attempt to unify some
common algorithms and apply them in a unique way to
improve the current state of the art used for company
name searching.
In addition to traditional string matching approaches
(based on syntax) the system adopts other approaches
based on semantic similarity of company names. Given
a query term (proposed company name), we can rank
similar existing company names based on spelling,
meaning and other factors. Matching algorithms will
run sequentially with phonetic (double metaphone) and
semantic (synonym substitution) methods to compute
an overall similarity score between terms. By applying
all of these techniques the accuracy of the system can
be improved over traditional approaches. A test data set
has been collected and is used to measure the
effectiveness of each algorithm. Furthermore, by
separating the main matching engines into distributed
services performance and scalability can be ensured.
4. Architecture &Design
System performance and scalability are considered
of high priority in the success of the ROSE system and
the architecture has been designed to maximize this by
Utilising the .Net frameworks CLR integration
to compile complex C# code as managed code
within the database
The most CPU intensive procedures have been
designed as separate services that can be run
independently of each other and on separate
machines. This greatly increases scalability.
ROSE Interface
Results Weighting
Service
Semantic Search
Service
Phonetic Search
Service
Orthographic Search
Service
Database
5. Conclusion
To date, competitive performance (accuracy) and
efficiency has been achieved on several of the
individual components. Methods to combine evidence
from the multiple approaches are currently being
evaluated.
6. References
[1] Amending Directives 89/666/EEC, 2005/56/EC and
2009/101/EC as regards the interconnection of central,
commercial and companies’ registers.
[2] Europa Press release: IP/11/221