Comparing the Performance of Information Retrieval of Semantic and Keyword Search Engines Based on Phrase Search

Bahari Varzaneh, Hosein Comparing the Performance of Information Retrieval of Semantic and Keyword Search Engines Based on Phrase Search. Journal of Knowledge-Research Studies, 2022, vol. 1, n. 2, pp. 102-117. [Journal article (Paginated)]

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English abstract

Purpose: The aim of the research is to compare the performance of Information Retrieval of semantic and keyword search engines based on phrase search (simple & complex). Methodology: The present applied and semi-experimental research community includes all active search engines on the web. Research samples were selected based on stratified random sampling and purposive sampling. The data collection tool of two researcher-made checklists includes ten simple and complex phrase queries. Findings: Bing and Cluuz (with similar precision of 53%), DuckDuckGo, and Yahoo were the most accurate in searching for simple phrases, respectively. Bing, DuckDuckGo, Yahoo, and Cluuz were the most accurate in their search for complex terms, respectively. In general, Bing, DuckDuckGo, Cluuz and Yahoo have the highest precision, respectively. Also, the average total precision of keyword search engines is more heightened than semantic search engines. Conclusion: The Bing keyword search engine performs better than the other three semantic search engines and other keywords. Semantic search engines claim to have more capabilities in retrieving relevant information than keyword search engines. But in this study, it was found that Cluuz and DuckDuckGo do not excel in search terms over keyword search engines. These tools did not perform as well as semantic web search engines, and it seems that they have a long way to go to become real semantic search engines. And to achieve this, it is necessary to use the facilities, tools, modules, and emerging technologies of the new age, such as machine learning, deep learning, combining these modules with pervasive techniques, data mining, etc. Value: So far, not been compared the phrase search performance in the sample semantic and keyword search engines. And in this regard, the researcher has tried to achieve an actual result with an exact Survey.

['eprint_fieldopt_linguabib_' not defined] abstract

هدف: هدف از انجام این پژوهش مقایسه عملکرد بازیابی اطلاعات موتورهای جستجوی معنایی و کلیدواژه بر اساس جستجوی عبارت (ساده و پیچیده) است. روش‌شناسی‌: جامعه پژوهش کاربردی و نیمه تجربی حاضر شامل تمام موتورهای جستجوی فعال در وب است. نمونه‌های پژوهش بر اساس نمونه‌گیری طبقه‌ای تصادفی و نمونه‌گیری هدفمند انتخاب شدند. ابزار گردآوری داده‌های دو چک‌لیست محقق ساخته شامل 10 پرس و جوی عبارتی ساده و پیچیده است. یافته‌ها: بینگ و کلاز (با میزان دقت مشابه 53% )، داک‌داک‌گو و یاهو به ترتیب بیشترین دقت را در جستجوی عبارات ساده داشتند. در جستجوی عبارات پیچیده نیز به ترتیب بینگ، داک‌داک‌گو، یاهو و کلاز بیشترین میزان دقت را داشتند. به‌طورکلی، بینگ، داک‌داک‌گو، کلاز و یاهو به ترتیب بیشترین میزان دقت را دارند. همچنین، میزان میانگین کل دقت موتورهای جستجوی کلیدواژه‌ای از موتورهای جستجوی معنایی بیشتر است. نتایج: موتور جستجوی کلیدواژه‌ای بینگ بهترین عملکرد را نسبت به سه موتور جستجوی معنایی و کلیدواژه‌ای دیگر دارد. موتورهای جستجوی معنایی بااینکه مدعی هستند توانایی‌های بیشتری در بازیابی اطلاعات مرتبط نسبت به موتورهای جستجوی کلیدواژه‌ای دارند اما در این بررسی مشخص شد کلاز و داک‌داک‌گو در جستجوی عبارتی نسبت به موتورهای جستجوی کلیدواژه‌ای برتری ندارند. این ابزارها به‌عنوان موتورهای جستجوی وب معنایی عملکرد قابل قبولی از خود نشان ندادند و به نظر می‌رسد باید مسیر طولانی را طی نمایند تا به موتورهای جستجوی معنایی واقعی تبدیل شوند و برای نیل به این مهم لازم است از امکانات، ابزارها، ماژول‌ها، و فناوری‌های نوظهور عصر جدید از قبیل یادگیری ماشین، یادگیری عمیق، تلفیق این ماژول‌ها با تکنیک‌های متن‌کاوی، داده‌کاوی، و... بهره گیرند. اصالت: تاکنون در موتورهای جستجوی معنایی و کلیدواژه‌ای نمونه، عملکرد جستجوی عبارتی مقایسه نشده است. و در این راستا، پژوهشگر تلاش کرده است تا با یک بررسی دقیق به یک نتیجه واقعی دست یابد تا موتور جستجوی قدرتمند در این نوع جستجو را به کاربران معرفی کند.

Item type: Journal article (Paginated)
Keywords: Information Retrieval; Phrase Search; Performance; Keyword Search Engines; Semantic Search Engines
Subjects: L. Information technology and library technology > LZ. None of these, but in this section.
Depositing user: Rasoul Zavaraqi
Date deposited: 22 Sep 2022 20:03
Last modified: 22 Sep 2022 20:03
URI: http://hdl.handle.net/10760/43543

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