Thoughts about disordered thinking: measuring and quantifying the laws of order and disorder

Peer ReviewedPostprint (author's final draft

U-INVITE: Estimating Individual Semantic Networks from Fluency Data

Semantic networks have been used extensively in psychologyto describe how humans organize facts and knowledge inmemory. Numerous methods have been proposed to constructsemantic networks using data from memory retrieval tasks,such as the semantic fluency task (listing items in a category).However these methods typically generate group-levelnetworks, and sometimes require a very large amount ofparticipant data. We present a novel computational methodfor estimating an individual’s semantic network usingsemantic fluency data that requires very little data. Weestablish its efficacy by examining the semantic relatedness ofassociations estimated by the model

Generation of learning paths in educational texts based on vocabulary co-occurrence networks in Wikipedia and randomness

We propose a new computational method for generating learning paths ineducational texts. The method relies on forming vocabulary co-occurrence networks amongarticles of Wikipedia online encyclopedia and exploiting random explorations to generateroute weighting parameters to form pedagogic co-occurrence networks. Motivated by previousresearch about scale-free small-world networks we suggest our networks to offer efficient andintuitive properties for knowledge representation and learning. In the context of cell biologywe provide experimental results about the properties of the linkage emerging in the vocabularyco-occurrence networks in a set of 175 Wikipedia articles and contrast it with the linkageemerging in the corresponding hyperlink network in Wikipedia. Furthermore we describeformation of the pedagogic co-occurrence network that can be exploited to recommendlearning paths for the student.Copyright by AACE. Reprinted from the Global Learn 2015: Global Conference on Learning and Technology with permission of AACE (http://www.aace.org)Peer reviewe

Supporting online health queries by modeling patterns of creation, modification and retrieval of medical knowledge

We evaluated properties of knowledge resources that can be used for building new semantically and behaviorally motivated resources of health guidance and clinical decision making by modeling patterns of creation, modification and retrieval of medical knowledge. We evaluated statistical properties of Wikipedia articles of general terminology and medical terminology based on 25 most common diagnosis names emerging in an electronic health records system. We also evaluated statistical properties of general terminology used in everyday life in respect to occurrence and importance to enable adaptive perspectives to medical knowledge. Our experiments exploit a conceptual co-occurrence network that we created based on a set of 93 medical texts about healthcare guidelines provided by The Finnish Medical Society Duodecim containing 57 679 unique conceptual links. We provide supplementing statistics of an extended range of Wikipedia articles and an n-gram analysis about the set of medical texts.Peer reviewe

Educational exploration along the shortest paths in conceptual networks based on co-occurrence, language ability levels and frequency ranking

We propose a new computational method to support learning that relies on adaptiveexploration of the shortest paths in conceptual networks that have been formed based on cooccurrencesof concepts in suitable text samples and selecting concepts corresponding todesired language ability levels and frequency ranking. Relying on Google Web 1T 5-gramdatabase we have built a conceptual co-occurrence network reaching the coverage of 3018unique concepts and 54 610 unique pairs of co-occurring concepts thus approximatelymatching with a vocabulary size suggested to be enough for sufficient comprehension andwith the highest language ability levels of English Vocabulary Profile. Our method offers tothe learner recommendations about suitable exploration paths along the shortest connectingpaths between the concepts belonging to a desired learning topic vocabulary, computed withYen's algorithm. By indicating for each concept the language ability level and the frequencyranking position in British National Corpus enables to prioritize such shortest paths ofconcepts that most best match the current suitable comprehension level of the learner. Ourpreliminary experiment showed that the method can pedagogically intuitively supportcumulative adoption of knowledge in the context of study entities belonging to a corecurriculum. Relying on our research we are opening a free educational resource athttp://www.freelearningpath.org that enables learners and educators to get adaptive guidancefor exploring a desired educational content.Peer reviewe

Vector-based Approach to Verbal Cognition

Human verbal thinking is an object of many multidisciplinary studies Verbal cognition is often an integration of complex mental activities such as neurocognitive and psychological processes In neuro-cognitive study of language neural architecture and neuropsychological mechanism of verbal cognition are basis of a vector based modeling Human mental states as constituents of mental continuum represent an infinite set of meanings Number of meanings is not limited but numbers of words and rules that are used for building complex verbal structures are limited Verbal perception and interpretation of the multiple meanings and propositions in mental continuum can be modeled by applying tensor methods A comparison of human mental space to a vector space is an effective way of analyzing of human semantic vocabulary mental representations and rules of clustering and mapping As such Euclidean and non-Euclidean spaces can be applied for a description of human semantic vocabulary and high order Additionally changes in semantics and structures can be analyzed in 3D and other dimensional spaces It is suggested that different forms of verbal representation should be analyzed in a light of vector tensor transformations Vector dot and cross product covariance and contra variance have been applied to analysis of semantic transformations and pragmatic change in high order syntax structures These ideas are supported by empirical data from typologically different languages such as Mongolian English and Russian Moreover the author argues that the vectorbased approach to cognitive linguistics offers new opportunities to develop an alternative version of quantitative semantics and thus to extend theory of Universal grammar in new dimension

Educational exploration based on conceptual networks generated by students and Wikipedia linkage

We propose a new educational framework for educational exploration basedon conceptual networks generated and explored by students supplied with Wikipedialinkage. In the first experimental setup we had a group of students (n=103) to createhigh-frequency lists of words and links between words, and in the second experimentalsetup we had another group of students (n=49) to explore a subsection of hyperlinknetwork of the Wikipedia corresponding to conceptual networks generated by students inthe first experimental setup. We report findings based on comparison of word lists andconceptual networks generated by students, vocabulary ranking of British NationalCorpus, hyperlink network structure of the Wikipedia and exploration paths of studentsin the hyperlink network of the Wikipedia. After traversing 20 hyperlink steps eachstudent could recall on average about 33,1 percent of unique shown concepts and onaverage 64,8 percent of unique selected concepts which seems to indicate thatexploration in hyperlink network can support adoption of new knowledge.Peer reviewe