Nowadays, according to the increasingly increasing information, the\nimportance of its presentation is also increasing. The internet has become one\nof the main sources of information for users and their favorite topics. It also\nprovides access to more information. Understanding this information is very\nimportant for providing the best set of information resources for users.\nContent providers now need a precise and efficient way to retrieve news with\nthe least human help. Data mining has led to the emergence of new methods for\ndetecting related and unrelated documents. Although the conceptual relationship\nbetween documents may be negligible, it is important to provide useful\ninformation and relevant content to users. In this paper, a new approach based\non the Combination of Features (CoF) for information retrieval operations is\nintroduced. Along with introducing this new approach, we proposed a dataset by\nidentifying the most commonly used keywords in documents and using the most\nappropriate documents to help them with the abundance of vocabulary. Then,\nusing the proposed approach, techniques of text categorization, evaluation\ncriteria and ranking algorithms, the data were analyzed and examined. The\nevaluation results show that using the combination of features approach\nimproves the quality and effects on efficient ranking.\n