Improving the effectiveness of information retrieval system under vector space model using adaptive genetic algorithm

مقدم أطروحة جامعية

Maayitah, Wafa Zaal Muhammad

مشرف أطروحة جامعية

al-Rababiah, Mamun S.
Kanan, Ghassan Jaddu

أعضاء اللجنة

al-Nihoud, Jihad Quball Awdah
al-Smadi, Adnan M.
al-Shalabi, Riyad

الجامعة

جامعة آل البيت

الكلية

كلية الأمير الحسين بن عبد الله لتكنولوجيا المعلومات

القسم الأكاديمي

قسم علوم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2010

الملخص الإنجليزي

Traditional Genetic Algorithm which is used in previous studies depends on fixed control parameters especially crossover and mutation probabilities, but in this research we tried to use adaptive genetic algorithm. Genetic algorithm started to be applied in information retrieval system in order to optimize the query by genetic algorithm, a good query is a set of terms that express accurately the information need while being usable within collection corpus, the last part of this specification is critical for the matching process to be efficient, that is why most research efforts are actually put toward the query improvement. We investigated the use of adaptive genetic algorithm (AGA) under vector space model, Extended Boolean model, and Language model in information retrieval (IR), the algorithm used crossover and mutation operators with variable probability, where a traditional genetic algorithm (GA) uses fixed values of those, and remain unchanged during execution.

GA is developed to support adaptive adjustment of mutation and crossover probability; this allows faster attainment of better solutions.

The research has been tested using 242 Arabic abstracts collected from the proceedings of the Saudi Arabian National conference.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• الخوارزميات
• استرجاع المعلومات

عدد الصفحات

55

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-310850