Implementation of an efficient Fuzzy Logic based Information Retrieval System

This paper exemplifies the implementation of an efficient Information Retrieval (IR) System to compute the similarity between a dataset and a query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query. Each query is assigned a score value based on its fuzzy similarity with the index keywords. The relevant documents are retrieved based on the score value. The performance and accuracy of the proposed fuzzy similarity model is compared with Cosine similarity model using Precision-Recall curves. The results prove the dominance of Fuzzy Similarity based IR system.Comment: arXiv admin note: substantial text overlap with http://ntz-develop.blogspot.in/ , http://www.micsymposium.org/mics2012/submissions/mics2012_submission_8.pdf , http://www.slideshare.net/JeffreyStricklandPhD/predictive-modeling-and-analytics-selectchapters-41304405 by other author

IRQX: A Framework for Information Retrieval Algorithms Using Query Expansion Techniques

The number of information retrieval users and their operations are continuously increasing with the rapid growth of internet technologies. Information Retrieval is one of the most prevalent operations that is frequently used by the Internet users. The process of Information Retrieval may cause two problems. First, the search engine may retrieve irrelevant documents and second it may fail to retrieve the relevant documents. Many approaches have been proposed to improve the query representation by reformulating the queries. Among them, Query Expansion (QE) is one of the most effective approaches. In Information Retrieval, Query Expansion is referred to as the techniques or algorithms that reformulate the original query by adding or modifying new terms into the query, in order to achieve better retrieval results. This paper contributed to the process of information retrieval algorithms using query expansion techniques to improve the precision and recall. The proposed framework Information Retrieval algorithms using Query Expansion (IRQX) facilitates the users to select their choice of algorithms based on their need

Fuzzy rule based profiling approach for enterprise information seeking and retrieval

With the exponential growth of information available on the Internet and various organisational intranets there is a need for profile based information seeking and retrieval (IS&R) systems. These systems should be able to support users with their context-aware information needs. This paper presents a new approach for enterprise IS&R systems using fuzzy logic to develop task, user and document profiles to model user information seeking behaviour. Relevance feedback was captured from real users engaged in IS&R tasks. The feedback was used to develop a linear regression model for predicting document relevancy based on implicit relevance indicators. Fuzzy relevance profiles were created using Term Frequency and Inverse Document Frequency (TF/IDF) analysis for the successful user queries. Fuzzy rule based summarisation was used to integrate the three profiles into a unified index reflecting the semantic weight of the query terms related to the task, user and document. The unified index was used to select the most relevant documents and experts related to the query topic. The overall performance of the system was evaluated based on standard precision and recall metrics which show significant improvements in retrieving relevant documents in response to user queries

A novel algorithm for the development of perceptual hashes based on extraction of attributes of biometric characteristics

S napretkom računalnih i mrežnih tehnologija, količina digitalnih slika koje se prenose ili pregledavaju putem digitalnih uređaja eksponencijalno raste, a u porastu je neovlaštena uporaba kao i krivotvorenje istih. Ovaj doktorski rad bavi se percepcijskim sažetcima koji su „otisak” digitalne slike izveden iz različitih atributa njezina sadržaja, a upotrebljavaju se za provjeru autentičnosti ili identifikaciju digitalnih slika. Postoji mnogo područja njihove primjene: zaštita autorskih prava, računalna forenzika ili pretraživanje baza slika. Njihove su prednosti mala veličina, brzo pretraživanje i slanje putem mreže te robusnost na manipulacije i modifikacije. U disertaciji je razvijen novi algoritam za izradu percepcijskih sažetaka, koji izdvaja i analizira, koristeći se metodom modificirane census transformacije, lokalne atribute interesnih regija slika odnosno biometrijskih uzoraka, a u svrhu ispitivanja mogućnosti njegove upotrebe u biometriji. Napravljena je usporedba s drugim najčešće korištenim algoritmima te se utvrđuje hoće li novorazvijeni algoritam biti točniji i robusniji u području biometrijske autentikacije.With the advancement of computer and network technologies, the amount of digital images which are transferred or browsed through digital devices increases exponentially. However, unauthorized use and counterfeiting of the same also increases. This doctoral thesis deals with the perceptual hashes which are a "print" of a digital image derived from various attributes of its contents, and which are used for authentication or identification of digital images. There are many areas of their application: protection of copyrights, computer forensics or searching image databases. Perceptual hashes have several advantages, such as a small size, fast searching and sending via the network as well as the robusness to manipulation and modification. In this thesis, an algorithm for making perceptual hashes which extract and analyze attributes of region of interest in an image for the possibility of their use in biometrics using methods of modified census transformation has been developed. A comparison has been made with other commonly used algorithms and an improved robusness and precision of the newly developed algorithm for the purpose of biometric authentication will be determined

A novel algorithm for the development of perceptual hashes based on extraction of attributes of biometric characteristics

S napretkom računalnih i mrežnih tehnologija, količina digitalnih slika koje se prenose ili pregledavaju putem digitalnih uređaja eksponencijalno raste, a u porastu je neovlaštena uporaba kao i krivotvorenje istih. Ovaj doktorski rad bavi se percepcijskim sažetcima koji su „otisak” digitalne slike izveden iz različitih atributa njezina sadržaja, a upotrebljavaju se za provjeru autentičnosti ili identifikaciju digitalnih slika. Postoji mnogo područja njihove primjene: zaštita autorskih prava, računalna forenzika ili pretraživanje baza slika. Njihove su prednosti mala veličina, brzo pretraživanje i slanje putem mreže te robusnost na manipulacije i modifikacije. U disertaciji je razvijen novi algoritam za izradu percepcijskih sažetaka, koji izdvaja i analizira, koristeći se metodom modificirane census transformacije, lokalne atribute interesnih regija slika odnosno biometrijskih uzoraka, a u svrhu ispitivanja mogućnosti njegove upotrebe u biometriji. Napravljena je usporedba s drugim najčešće korištenim algoritmima te se utvrđuje hoće li novorazvijeni algoritam biti točniji i robusniji u području biometrijske autentikacije.With the advancement of computer and network technologies, the amount of digital images which are transferred or browsed through digital devices increases exponentially. However, unauthorized use and counterfeiting of the same also increases. This doctoral thesis deals with the perceptual hashes which are a "print" of a digital image derived from various attributes of its contents, and which are used for authentication or identification of digital images. There are many areas of their application: protection of copyrights, computer forensics or searching image databases. Perceptual hashes have several advantages, such as a small size, fast searching and sending via the network as well as the robusness to manipulation and modification. In this thesis, an algorithm for making perceptual hashes which extract and analyze attributes of region of interest in an image for the possibility of their use in biometrics using methods of modified census transformation has been developed. A comparison has been made with other commonly used algorithms and an improved robusness and precision of the newly developed algorithm for the purpose of biometric authentication will be determined