Web Search Personalization Based on Browsing History by Artificial Immune System

Different users have different needs when they submit a query toa web search engine. Common search engines investigate the WorldWide Web (WWW) and find many pages according to user queryregardless the query submission. The aim of web searchpersonalization is to tailor search results for that particular user.One issue in this field is to gather user information without userintervention. Hence, this paper presents the insight of ArtificialImmune Systems (AIS) for user profile construction and probinghighly relevant pages in search results. From our investigations, wefound conclude that AIS is a suitable personalization tool toknowledge discovery due to its adaptability and learning capabilitythat are required to solve web search personalization.