A Full Text Retrieval System in a Digital Library Environment

Aruleba, Kehinde; Akomolafe, Dipo Theophilus; Afeni, Babajide Olakunle

doi:10.4236/iim.2016.81001

Cited by 8 publications

(8 citation statements)

References 9 publications

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“…The volume of information being created, generated and stored is huge. Without adequate knowledge of Information Retrieval (IR) methods, the retrieval & predictive process for information would be cumbersome and frustrating [6]. They further studied the concept of existing information retrieval models, and the knowledge acquired was used to design a digital library information retrieval system.…”

Section: Related Workmentioning

confidence: 99%

An Improved Traffic Crime Predictive System using Multinomial Naive Bayes Text Classification Algorithm

A.¹,

V.O.²,

Ugwu³

2019

IJCA

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Traffic law enforcement agencies in Nigeria have faced a huge setback as they do not have records of offenders or criminals that have been persecuted in the past. In this paper, a system was developed that can predict the possible class of traffic crime together with the penalty attached to that class of criminal offence that a known traffic criminal offender is most likely to commit next. The likelihood and frequency table will be constructed from a dataset of traffic crime data, the likelihood of a user falling under a particular class of traffic crime will also be established. Also, proposed to be designed and developed is a predictive system that uses object-oriented analysis and design methodology (OOADM), improved naïve bayes text classification algorithm to solve these problems. This will be achieved by implementing the stated model with python model-view-controller (MVC) framework known as Django Framework. This improved system is implemented using a real-time, cloud-hosted NOSQL database called FireBase which guarantees scalability. From the results, it was found out that the speed and predictability of probability of any user falling under a class 1 crime type was 81.42% and 10.39%, 8.19% for class 2 and class 3 respectively.

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Section: Related Workmentioning

confidence: 99%

An Improved Traffic Crime Predictive System using Multinomial Naive Bayes Text Classification Algorithm

A.¹,

V.O.²,

Ugwu³

2019

IJCA

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“…Materials are digitalized to improve their online accessibility, sorting, transmission and retrieval. Digitization refers to the process of converting print media to the digital content for electronic storage, access, and distribution among users [3]. The digitization process has facilitated storage and enhanced ease manipulation of the traditionally digitized content by researchers [25].…”

Section: Literature Review 21 Digitizationmentioning

confidence: 99%

“…The frequent use of the internet among the researchers has slowed the usage of the library catalogs since they lack most of web 2.0 features such as relevancy ranking [12]. The huge unstructured and amorphous data available in the digital library databases has on the other hand made it difficult for developers to come up with algorithms for enhancing successful information retrieval that matches the user queries [3]. In their study Kumar & Vohra [9] established that 12.5 % of the library users at Guru Nanak Dev University found the OPAC catalogue to be slow and complicated to use thus they needed help from librarians.…”

Section: Opac Catalogmentioning

confidence: 99%

Text Mining in Digital Libraries using OKAPI BM25 Model

Tinega¹,

Mwangi²,

Rimiru³

2018

IJCATR

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The emergence of the internet has made vast amounts of information available and easily accessible online. As a result, most libraries have digitized their content in order to remain relevant to their users and to keep pace with the advancement of the internet. However, these digital libraries have been criticized for using inefficient information retrieval models that do not perform relevance ranking to the retrieved results. This paper proposed the use of OKAPI BM25 model in text mining so as means of improving relevance ranking of digital libraries. Okapi BM25 model was selected because it is a probability-based relevance ranking algorithm. A case study research was conducted and the model design was based on information retrieval processes. The performance of Boolean, vector space, and Okapi BM25 models was compared for data retrieval. Relevant ranked documents were retrieved and displayed at the OPAC framework search page. The results revealed that Okapi BM 25 outperformed Boolean model and Vector Space model. Therefore, this paper proposes the use of Okapi BM25 model to reward terms according to their relative frequencies in a document so as to improve the performance of text mining in digital libraries.

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“…Berupa proses menampilkan, mencari, dan memanipulasi kumpulan data teks elektronik yang besar dan mungkin tidak terstruktur. merupakan tanggapan atas serangkaian perintah query [4].…”

Section: Pendahuluanunclassified

Analisa Perbandingan Query Pencarian Menggunakan Fungsi Match-Against Pada Mysql Dengan Tabel Kamus

Pratama¹,

Hudha²,

Prayoghi³

2018

ccitj

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Virtually all database-related systems provide search features. Starting from a complex search engine like google to a relatively simple example of search features on a digital library page. A good search engine is capable of delivering fast, accurate, and fault-tolerant results. Speed may be affected by server device capabilities and complex algorithm combinations.The form of the condition condition used in the search query generally uses LIKE for partial search, REGEXP for multi key search, and MATCH-AGAINST for multi key search with fulltext index. However, these functions are not sufficient to perform a search selection on a slightly wrong key or rather fault tolerance that is still not good. So researchers do an analysis if one of the search function is combined with a dictionary table.Table dictionary as a comparator key to find a more appropriate key if key wrong key. But on the other hand the addition of the comparison process is estimated to have a weakness to the processing time. Researchers assume if the weakness can be overcome if the ability of the server is improved.

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A Full Text Retrieval System in a Digital Library Environment

Cited by 8 publications

References 9 publications

An Improved Traffic Crime Predictive System using Multinomial Naive Bayes Text Classification Algorithm

An Improved Traffic Crime Predictive System using Multinomial Naive Bayes Text Classification Algorithm

Text Mining in Digital Libraries using OKAPI BM25 Model

Analisa Perbandingan Query Pencarian Menggunakan Fungsi Match-Against Pada Mysql Dengan Tabel Kamus

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