Natural language processing in information retrieval

Doszkocs, Tamas E.

doi:10.1002/asi.4630370405

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Many ways of achieving feedback have been tested in IR systems [21] and are being developed in OPACs [2,22,23].…”

Section: Relevance Feedbackmentioning

confidence: 99%

Relevance as an aid to evaluation in OPACs

O’Brien

1990

Journal of Information Science

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The relevance of retrieved documents or document descriptions has been a central measurement in the evaluation of information retrieval (IR) systems. Online public access catalogues (OPACs) are sirrular in many ways and so relevance should be an appropnate evaluation tool in measuring their performance. The development of relevance in evaluating IR systems is described and also the important differences between such systems and OPACs. Characteristics of the endusers of both systems are discussed with the conclusion that end-users' motivation and behaviour are as yet not fully understood. The implication of this is that relevance is a central feature, but only one, of an OPAC user's overall information need.

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“…Many ways of achieving feedback have been tested in IR systems [21] and are being developed in OPACs [2,22,23].…”

Section: Relevance Feedbackmentioning

confidence: 99%

Relevance as an aid to evaluation in OPACs

O’Brien

1990

Journal of Information Science

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“…Similarly, the IRS is more user-friendly if the estimated relevance levels of the documents are supplied in a linguistic form (e.g., linguistic terms such as "relevant," "very relevant," may be used) rather than with scores. Following these ideas (Bordogna & Pasi, 1993), several fuzzy linguistic IRSs have been proposed using a fuzzy linguistic approach (Zadeh, 1975) to model the weights in the query and evaluation subsystems (Biswas, Bezdek, Subramanian, & Marques, 1987a, 1987bBolc, Kowalski, & Kozlowska, 1985;Bordogna & Pasi, 1993, 1995aDoszkocs, 1986;Kraft, Bordogna, & Pasi, 1994). In this context, the ordinal fuzzy linguistic approach (Delgado, Verdegay, & Vila, 1993;Herrera & Herrera-Viedma, 1997;Herrera, Herrera-Viedma, & Verdegay, 1996b) is a linguistic approach that allows us to overcome the limitations of the classical fuzzy linguistic approach (Zadeh, 1975), i.e., we do not have to explicitly establish semantic rules or syntactic rules (e.g., using a context-free grammar), thereby reducing, the complexity of the design for the IRS.…”

Section: Introductionmentioning

confidence: 99%

Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach

Liu

2001

J. Am. Soc. Inf. Sci.

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A linguistic model for an Information Retrieval System (IRS) defined using an ordinal fuzzy linguistic approach is proposed. The ordinal fuzzy linguistic approach is presented, and its use for modeling the imprecision and subjectivity that appear in the user-IRS interaction is studied. The user queries and IRS responses are modeled linguistically using the concept of fuzzy linguistic variables. The system accepts Boolean queries whose terms can be weighted simultaneously by means of ordinal linguistic values according to three possible semantics: a symmetrical threshold semantic, a quantitative semantic, and an importance semantic. The first one identifies a new threshold semantic used to express qualitative restrictions on the documents retrieved for a given term. It is monotone increasing in index term weight for the threshold values that are on the right of the mid-value, and decreasing for the threshold values that are on the left of the mid-value. The second one is a new semantic proposal introduced to express quantitative restrictions on the documents retrieved for a term, i.e., restrictions on the number of documents that must be retrieved containing that term. The last one is the usual semantic of relative importance that has an effect when the term is in a Boolean expression. A bottom-up evaluation mechanism of queries is presented that coherently integrates the use of the three semantics and satisfies the separability property. The advantage of this IRS with respect to others is that users can express linguistically different semantic restrictions on the desired documents simultaneously, incorporating more flexibility in the user-IRS interaction.

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Metin Sınıflandırması için Geleneksel Makine Öğrenimi ve Dönüştürücü Tabanlı Derin Öğrenme Modellerinin Karşılaştırmalı Analizi

Aydın,

Erdem,

Tekerek

2024

Journal of Polytechnic

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Günümüz bilgi çağında, büyük miktarda metinsel verinin üretilmesi ve kullanılması son derece önemli hale gelmiştir. Yapay zeka alanında, özellikle doğal dil işleme içerisinde, metin sınıflandırma bu veri selinin düzenlenmesine ve anlaşılmasına yardımcı olan kritik bir görev olarak öne çıkar. Metin sınıflandırmanın özü, metin parçalarını kategorilere ayırarak bunları ilgili sınıflara tahsis etmektir, bu süreç, makine öğrenimi ve derin öğrenme metodlarıyla önemli ölçüde ilerletilmiştir. Bu çalışmanın amacı, Geleneksel Makine Öğrenimi teknikleri arasında Karar Ağacı, Naive Bayes, Rastgele Orman ve SVM gibi tekniklerin etkinliğini değerlendirmek, ayrıca DistilBERT, BERT, GPT-2, RoBERTa ve GPT-3 gibi son teknoloji Transformer tabanlı modellerin metin sınıflandırma görevlerindeki performansını değerlendirmektir. Bulgular, Naive Bayes'in geleneksel yöntemler arasında %65'lik bir doğruluk oranına ulaştığını gösterirken, GPT-3'ün onları %77 daha yüksek bir doğruluk ve F1 skoru ile aştığını ortaya koymaktadır. Bu sonuçlar, Transformer tabanlı modellerin metin sınıflandırma çabalarında önemli vaatler ve etkinliklerini vurgulamaktadır.

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Natural language processing in information retrieval

Cited by 3 publications

References 14 publications

Relevance as an aid to evaluation in OPACs

Relevance as an aid to evaluation in OPACs

Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach

Metin Sınıflandırması için Geleneksel Makine Öğrenimi ve Dönüştürücü Tabanlı Derin Öğrenme Modellerinin Karşılaştırmalı Analizi

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