In today’s digital era, information can be easily acquired from various sources, and is available in many different forms, which include data, text, image, voice, and signal. However, disparate information needs to be processed meticulously and intelligently for it to be useful. In this aspect, intelligent information processing systems play an important role to help extract meaningful and significant information from spurious one, and to help decision makers to make informed decisions. Over the years, researchers have designed and developed a variety of intelligent information processing techniques, and have demonstrated their applicability to undertaking various complex problems. In this special issue, a total of seven articles in the general area of intelligent information processing are presented. It should be noted that these articles represent only a small part of the huge research activities in this exciting and fast growing area. The main aim is to highlight some recent advances in different intelligent information processing techniques and their applications, ranging from natural language processing, affective computing, data mining, to fuzzy information processing. The first and second articles are concerned with natural language processing and affective computing. In the first article, an intelligent natural language processing technique that allows a machine to detect illogical word combinations is described. A knowledge model of human discourse and words, focusing on nouns and adjective phrases, is created. Using a tree-like structure, the knowledge model is used to form general properties of objects. An association model is then used to form word-to-word relationships based on a