The Impact of Ontology on the Performance of Information Retrieval

2008 ◽  
Vol 3 (1) ◽  
pp. 24-37 ◽  
Author(s):  
Maria Indrawan ◽  
Seng W. Loke
Keyword(s):  
Information Retrieval ◽  
The Impact

scholarly journals Assessing the Impact of Stemming Algorithms Applied to Brazilian Legislative Documents Retrieval

2021 ◽  
Author(s):  
Ellen Souza ◽  
Gyovana Moriyama ◽  
Douglas Vitório ◽  
André C. P. L. F. de Carvalho ◽  
Nádia Félix ◽  
...  
Keyword(s):  
Information Retrieval ◽  
The Impact ◽  
Field Area ◽  
Chamber Of Deputies

The main purpose of stemming is to reduce the inflected words into its root form or stem. Thus, words can be mapped to the same concept, improving the process of information retrieval, regarding its ability to index documents and to reduce data dimensionality. However, the efficiency of those algorithms varies according to different aspects. Also, studies in the field area reached contrasting conclusions. This work assesses the use of stemmers in the retrieval of legislative documents written in Portuguese. Four stemmers together with BM25 were evaluated in two legislative corpora from the Brazilian Chamber of Deputies. RSLP-S and Savoy stemmers showed the best improvements in the information retrieval pipeline.

scholarly journals An Empirical Prediction Methodology for the Emotional Behaviors with the Impact of Musical Features

2020 ◽  
Vol 9 (6) ◽  
pp. 646-649
Keyword(s):  
Feature Extraction ◽  
Information Retrieval ◽  
Real Situation ◽  
Linguistic Information ◽  
Empirical Prediction ◽  
Current State ◽  
Pragmatic Analysis ◽  
State Of Mind ◽  
Music Information ◽  
The Impact

Music is the combination of melody, linguistic information and singer’s mental realm. As popularity of music increases, the choice of songs also varies according to their mental conditions. The mental conditions reach the supreme bliss to melancholy strain based on the musical notes. Majority mostly prefer songs, which satisfy their current state of mind. Pragmatic analysis in music by computer is a difficult task, as emotion is very complex and it camouflages the real situation. Hence, In this paper , trying to classify the songs based on the features of music which helps to classify the emotion more easily. Music feature extraction is done using Music Information Retrieval (MIR) toolbox. The dataset consists of 100 of Hindi songs of 30 seconds clip and later classify the emotion based on Naïve Bayes classification method using Weka API.

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