افزایش سرعت جستجو در مدل‌‌های مبتنی بر مجاورت
محورهای موضوعی : مهندسی برق و کامپیوترجواد پاک‌سيما 1 , علي‌محمد زارع بيدكي 2 , ولي درهمي 3
1 - دانشگاه يزد
2 - دانشگاه يزد
3 - دانشگاه يزد
کلید واژه: موتور جستجو رتبه‌بندی فاصله مدل مجاورت سرعت بازیابی,
چکیده مقاله :
یکی از اصلی‌‌ترین چالش‌‌های مدل‌‌های مبتنی بر مجاورت مسأله سرعت بازیابی اطلاعات می‌‌باشد. در مدل‌‌های مبتنی بر مجاورت مفهومی به نام فاصله تعریف می‌‌شود که برای محاسبه آن باید موقعیت کلمات پرس و جو در سند استخراج شود. این موضوع یعنی استخراج موقعیت‌‌ها و محاسبه فاصله‌‌ها فرایندی زمان‌‌بر است و چون غالباً در زمان جستجو اجرا می‌‌شود از دید کاربر اهمیت بیشتری دارد. در صورتی که بتوان تعداد اسناد مورد بررسی را کاهش داد بازیابی سریع‌‌تر می‌‌شود. در این مقاله الگوریتمی به نام 3SNTK برای هرس‌کردن پویای اسناد در موقع جستجوی عبارت ارائه گردیده است. برای اجتناب از تخصیص بیش از حد حافظه و کاهش ریسک بروز خطا در موقع بازیابی، امتیاز تعدادی از اسناد بدون هیچ گونه هرسی محاسبه می‌‌شود (Skip-N). در این الگوریتم از سه هرم حداقل برای استخراج اسناد دارای بالاترین امتیازها استفاده شده و آزمایش‌‌ها نشان می‌‌دهد که استفاده از الگوریتم پیشنهادی باعث بهبود سرعت بازیابی می‌‌گردد.
One of the main challenges in the proximity models is the speed of data retrieval. These models define a distance concept which is calculated based on the positions of query terms in the documents. This means that finding the positions and calculating the distance is a time consuming process and because it usually executed during the search time it has a special importance to users. If we can reduce the number of documents, retrieval process becomes faster. In this paper, the SNTK3 algorithm is proposed to prune documents dynamically. To avoid allocating too much memory and reducing the risk of errors during the retrieval, some documents' scores are calculated without any pruning (Skip-N). The SNTK3 algorithm uses three pyramids to extract documents with the highest scores. Experiments show that the proposed algorithm can improve the speed of retrieval.
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