IMPROVING TEXT MINING METHODS IN MARKET PREDICTION VIA PROTOTYPE SELECTION ALGORITHMS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NIKNAM FARZAD; NIKNAFS ALI AKBAR

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download Full-Text

Persian Verion

View:

1,429

Download:

Cites:

Information Journal Paper

Title

IMPROVING TEXT MINING METHODS IN MARKET PREDICTION VIA PROTOTYPE SELECTION ALGORITHMS

Author(s)

NIKNAM FARZAD | NIKNAFS ALI AKBAR | Issue Writer Certificate

Keywords

PROTOTYPE SELECTIONQ1

MARKET PREDICTIONQ1

TEXT CLASSIFICATIONQ1

TEXT MININGQ1

Abstract

Nowadays, researches are faced with large volumes of data. Since a considerable amount of them are unstructured, they cannot be processed naturally. Hence two main challenges in this field are high dimensional of features space and bulk of available data. In this research, a feature selection method based on target features is propose to handle the curse of dimensionality. Moreover, to address the huge volume of data some of PROTOTYPE SELECTION approaches are utilized. The proposed method in this paper has three essential steps that each step improves the previous ones. Although, the proposed method reached significant results in each phase separately, its best performance obtained via the last phase in terms of classification accuracy rate. To evaluate the performance of the proposed method, it has been compared with three-layer algorithm. The results revealed that the proposed method had significantly better results than the three-layer algorithm in average.

Cites

No record.

References

No record.

Cite

APA: Copy

NIKNAM, FARZAD, & NIKNAFS, ALI AKBAR. (2016). IMPROVING TEXT MINING METHODS IN MARKET PREDICTION VIA PROTOTYPE SELECTION ALGORITHMS. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, 8(2 ), 415-434. SID. https://sid.ir/paper/140444/en

Vancouver: Copy

NIKNAM FARZAD, NIKNAFS ALI AKBAR. IMPROVING TEXT MINING METHODS IN MARKET PREDICTION VIA PROTOTYPE SELECTION ALGORITHMS. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT[Internet]. 2016;8(2 ):415-434. Available from: https://sid.ir/paper/140444/en

IEEE: Copy

FARZAD NIKNAM, and ALI AKBAR NIKNAFS, “IMPROVING TEXT MINING METHODS IN MARKET PREDICTION VIA PROTOTYPE SELECTION ALGORITHMS,” JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, vol. 8, no. 2 , pp. 415–434, 2016, [Online]. Available: https://sid.ir/paper/140444/en

Related Journal Papers