Some humorous texts can be detected by stereotyped patterns and terminology. But a humorous story or situation is often an exaggeration of patterns that also occur in serious texts: novelty, unusual plot twists, and situations that disrupt normal social conventions. The same methods for detecting novelty in serious texts can be adapted to detecting novelty in a humorous situation, but with additional tests for features that make it humorous. To interpret and reason about natural language texts, VivoMind Research has developed a cognitive architecture based on societies of heterogeneous intercommunicating agents that use conceptual graphs (CGs) as the knowledge representation. CGs are designed for representing semantics at the level of sentences and paragraphs, but they must be related to larger patterns that span an entire story, article, or book. For detecting and analyzing large-scale patterns, catastrophe theoretical semantics has proved to be surprisingly effective. This article discusses applications to both fictional and nonfictional documents of various kinds, both serious and humorous.

The fable of Hansel and Gretel describes the plight of two children over two types of threat; harm to their immediate survival and pain from hunger. The two contexts of self-preservation and feeding are evident from the flow of the story dialog, therefore an automatic re-playing of dialog can be realized by picking sentences from two lists; one containing sentences in the context of self-preservation, the other in the context of feeding. Theory and Internet humor appreciation surveys suggest that humorous sentences in the context of self-preservation have relatively constant preference with respect to age, while in the context of hunger and protection of feeding turf to decline with age, reflecting the reduced need for food with aging. Sentences in the context of sociosexual relationships increased in preference until adulthood then declined with maturity. Also, sentences in parenting context, such as when caring for offspring, society and the environment were found to increase in preference with age and maturity. Therefore in order to construct a recursive Hansel and Gretel dialog for audience of all ages, two lists of sentences are added to feeding: In sociosexual and parenting contexts. The self-preservation list is paired with one of the remaining three, representing three stages of age; youth, adulthood and maturity. The single thread story of Hansel and Gretel serves as a template for recursive dialog, making it possible to create alternative threads and unbound possibilities for plots, thereby duplicating the story structure without repeating the narrative.

Patients with schizophrenia are characterized by humor recognition deficit which is connected with their cognitive disorder such as inability to filter out irrelevant stimuli. As soon as patients with schizotypal and affective disorders easily recognize humor, this may be used as a strong diagnostic criterion in clinical practice. On the other hand humor recognition by artificial intellect became a hot question in computer science in a flow of attempts to bring human-computer communication closer to social. It is argued that schizophrenic and computer thinking have common features. Both have lack of social and emotional context understanding. To compare failures in humor recognition made by patients with schizophrenia vs computer may move forward theory and practice of both clinical psychology and computer science.

Humor employs an essential false logic which masks the incongruity of two central meanings that are brought into overlap. Formalizing this false logic—if it exists, exists intersubjectively, and is indeed essential for humor—to a degree that is sufficient for computational detection and generation of humor has been a vexing problem for computational humor research. This paper will outline several such logics, in addition to the default of reasoning in a way that is one degree more implausibly than the most common-sense logic that can connect two meanings. The results are not least influenced by a pilot study asking participants to explain different types of jokes.

In English, “puns” are usually perceived as a subclass of “jokes”. In Japanese, however, this is not necessarily true. In this paper we investigate whether Japanese native speakers perceive dajare (puns) as jooku (jokes). We first summarize existing research in the field of computational humor, both in English and Japanese, focusing on the usage of these two terms. This shows that in works of Japanese native speakers, puns are not commonly treated as jokes. Next we present some dictionary definitions of dajare and jooku, which show that they may actually be used in a similar manner to English. In order to study this issue, we conducted a survey, in which we asked Japanese participants three questions: whether they like jokes (jooku), whether they like puns (dajare) and whether dajare are jooku. The results showed that there is no common agreement regarding dajare being a genre of jokes. We analyze the outcome of this experiment and discuss them from different points of view.

This study presents a quantitative analysis of humor markers in computer-mediated communication (CMC). The data for this analysis consists of naturally occurring asynchronous CMC interactions from a public fan forum. Posts were tagged and coded as either humorous or non-humorous, and each individual humorous unit was coded as being one of 8 specific forms of humor. Next, each post was tagged and coded for the use of linguistic markers in the following categories: Punctuation, formatting, emoticons, laughter, and explicit. Descriptive and inferential statistics determined the following in the present data set: 1) Markers from each of the 5 marker categories occurred significantly more in humorous than non- humorous turns (p > 0.001); 2) Each of the 8 forms of humor present in the data were tested for the use of each marker-type, which suggests the existence of correlations between the iconic use of formatting in hyperbole (p > 0.001), the use of laughter in jocularity (p = 0.019) and insult (p = 0.024), and the use of emoticon in jocularity (p = 0.031); and 3) Humorous units which used humor markers gained significantly more humor response than unmarked humorous units (p > 0.001). These results provide a better understanding of features potentially related to the automated identification of humor.

The general goal of the symposium was to advance the state of the art in the direction of developing an AI system (the system) capable of understanding the mechanism of a joke at a level sufficient for providing a punch line to a human generated setup (even if unintentional) and conversely, for computer reacting competently to a human generated punch line that follows a setup, generated by either participant. The effort is multidisciplinary in nature, and the participants from several of the contributing disciplines, viz., computational semantics, knowledge representation, computational psychology, humanoid robotics, human-computer interface, human factors, to name just a few, took part in the work of the symposium.

An anticipated increase in the number of people withdementia will lead to an escalation in health and socialcare spending unless it is altered by a major breakthroughin treatment or prevention. Behavioral symptomsassociated with dementia (BSD) are some of themost difficult problems faced by caregivers. Severalmeasurement issues have hampered the progress oftimely intervention for BSD. Sensor technology mayoffer a solution to the early detection of BSD that willguide the development of tailored interventions. Similarly,a clinical conceptualization of BSD and its measurementissues can facilitate the engineering of sensornetworks and algorithms for activity recognition. Multidisciplinarycollaboration and the consideration of ethicalissues will improve the adoption of these technologiesin healthcare research.

Intelligent wheelchairs can help increase independent mobility for elderly residents with cognitive impairment, who are currently excluded from the use of powered wheelchairs. This paper presents three case studies, demonstrating the efficacy of the NOAH (Navigation and Obstacle Avoidance Help) system. The findings reported can be used to refine our understanding of user needs and help identify methods to improve the quality of life of the intended users.

Wandering is a problematic behavior that is common among people with dementia (PwD), and is highly influenced by the elders’ background and by contextual factors specific to the situation. We have developed the Ambient Augmented Memory System (AAMS) to support the caregiver to implement interventions based on providing external memory aids to the PwD. To provide a successful intervention, it is required to use an individualized approach that considers the context of the PwD situation. To reach this end, we extended the AAMS system to include an ontological model to support the context-aware tailoring of interventions for wandering. In this paper, we illustrate the ontology flexibility to personalize the AAMS system to support direct and indirect interventions for wandering through mobile devices.