Katarzyna Nowacka - Academia.edu (original) (raw)
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Papers by Katarzyna Nowacka
Fuzzy Sets and Systems, Aug 1, 2009
A new comprehensive model of information retrieval (IR) based on Zadeh's calculus of linguistic s... more A new comprehensive model of information retrieval (IR) based on Zadeh's calculus of linguistic statements is proposed. Its characteristic and novel feature is the capability to take into account both the imprecision and uncertainty pervading the textual information representation. It extends earlier IR models based on broadly meant fuzzy logic. Moreover, some techniques for indexing documents and queries in the framework of this model are proposed. The results of the computational experiments on standard document collections are reported.
Fuzzy Sets and Systems, 2009
Fuzzy logic (FL) and case-based reasoning (CBR) are two well-known techniques for the implementat... more Fuzzy logic (FL) and case-based reasoning (CBR) are two well-known techniques for the implementation of intelligent classification systems. Each technique has its own advantages and drawbacks. FL, for example, provides an intuitive user interface, simplifies the process of knowledge representation, and minimizes the system's computational complexity in terms of time and memory usage. On the other hand, FL has problems in knowledge elicitation which render it difficult to adopt for intelligent system implementation. CBR avoids these problems by making use of past input-output data to decide the system output for the present input. The accuracy of CBR system grows as the number of cases increase. However, more cases can mean added computational complexity in terms of space and time. In this paper we make the proposition that a hybrid system comprising a blend of FL and CBR can lead to a solution where the two approaches cover each other's weaknesses and benefit from each other's strengths. We support our claim by taking the problem of facial expression recognition from an input image. The facial expression recognition system presented in this paper uses a case base populated with fuzzy rules for recognizing each expression. Experimental results demonstrate that the system inherits the strengths of both methods.
… Processing Society, 2008. …, 2008
... Its functioning may be conveniently presented as follows: IOW ([v1,a1],...vn,an]) = m ∑ i=1wi... more ... Its functioning may be conveniently presented as follows: IOW ([v1,a1],...vn,an]) = m ∑ i=1wibi (22) where bi is the element ai accompanied by i-th largest value vi. ... d) Leximin: This is not a proper aggregation operator but rather a comparison operator. ...
Studies in Fuzziness and Soft Computing, 2010
Page 1. Using Fuzzy and Interval-Valued Fuzzy Sets in Automatic Text Categorization Based on a Fu... more Page 1. Using Fuzzy and Interval-Valued Fuzzy Sets in Automatic Text Categorization Based on a Fuzzy Information Retrieval Model S lawomir Zadro˙zny, Janusz Kacprzyk, and Katarzyna Nowacka Abstract. We consider the ...
2008 19th International Conference on Database and Expert Systems Applications, 2008
Fuzzy Sets and Systems, 2009
... It is defined by the formula IO W ([v 1 ,a 1 ], ...vm ,am ]) = m summationdisplay i=1 wibi (4... more ... It is defined by the formula IO W ([v 1 ,a 1 ], ...vm ,am ]) = m summationdisplay i=1 wibi (46) where bi is the element ai accompanied by i-th largest value ... Leximin: Let us assume two documentsd 1 and d 2 represented by linguistic statements X 1 is B 1 X m is B m and X 1 is C 1 ...
Lecture Notes in Computer Science, 2006
Fuzzy Sets and Systems, Aug 1, 2009
A new comprehensive model of information retrieval (IR) based on Zadeh's calculus of linguistic s... more A new comprehensive model of information retrieval (IR) based on Zadeh's calculus of linguistic statements is proposed. Its characteristic and novel feature is the capability to take into account both the imprecision and uncertainty pervading the textual information representation. It extends earlier IR models based on broadly meant fuzzy logic. Moreover, some techniques for indexing documents and queries in the framework of this model are proposed. The results of the computational experiments on standard document collections are reported.
Fuzzy Sets and Systems, 2009
Fuzzy logic (FL) and case-based reasoning (CBR) are two well-known techniques for the implementat... more Fuzzy logic (FL) and case-based reasoning (CBR) are two well-known techniques for the implementation of intelligent classification systems. Each technique has its own advantages and drawbacks. FL, for example, provides an intuitive user interface, simplifies the process of knowledge representation, and minimizes the system's computational complexity in terms of time and memory usage. On the other hand, FL has problems in knowledge elicitation which render it difficult to adopt for intelligent system implementation. CBR avoids these problems by making use of past input-output data to decide the system output for the present input. The accuracy of CBR system grows as the number of cases increase. However, more cases can mean added computational complexity in terms of space and time. In this paper we make the proposition that a hybrid system comprising a blend of FL and CBR can lead to a solution where the two approaches cover each other's weaknesses and benefit from each other's strengths. We support our claim by taking the problem of facial expression recognition from an input image. The facial expression recognition system presented in this paper uses a case base populated with fuzzy rules for recognizing each expression. Experimental results demonstrate that the system inherits the strengths of both methods.
… Processing Society, 2008. …, 2008
... Its functioning may be conveniently presented as follows: IOW ([v1,a1],...vn,an]) = m ∑ i=1wi... more ... Its functioning may be conveniently presented as follows: IOW ([v1,a1],...vn,an]) = m ∑ i=1wibi (22) where bi is the element ai accompanied by i-th largest value vi. ... d) Leximin: This is not a proper aggregation operator but rather a comparison operator. ...
Studies in Fuzziness and Soft Computing, 2010
Page 1. Using Fuzzy and Interval-Valued Fuzzy Sets in Automatic Text Categorization Based on a Fu... more Page 1. Using Fuzzy and Interval-Valued Fuzzy Sets in Automatic Text Categorization Based on a Fuzzy Information Retrieval Model S lawomir Zadro˙zny, Janusz Kacprzyk, and Katarzyna Nowacka Abstract. We consider the ...
2008 19th International Conference on Database and Expert Systems Applications, 2008
Fuzzy Sets and Systems, 2009
... It is defined by the formula IO W ([v 1 ,a 1 ], ...vm ,am ]) = m summationdisplay i=1 wibi (4... more ... It is defined by the formula IO W ([v 1 ,a 1 ], ...vm ,am ]) = m summationdisplay i=1 wibi (46) where bi is the element ai accompanied by i-th largest value ... Leximin: Let us assume two documentsd 1 and d 2 represented by linguistic statements X 1 is B 1 X m is B m and X 1 is C 1 ...
Lecture Notes in Computer Science, 2006