<i>WordNet: An electronic lexical database.</i> Christiane Fellbaum (Ed.). Cambridge,
MA: MIT Press, 1998. Pp. 423.

Oram, Peter

doi:10.1017/s0142716401221079

Cited by 25 publications

(9 citation statements)

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“…Individual words can have multiple meaning, thus can belong in multiple categories. A few popular lexical databases are LIWC (Pennebaker et al, 2015), MRC (Wilson, 1988), WordNet (Oram, 2001), Emolex (Mohammad & Turney, 2010). Li et al (2018) mapped users' posts into 126 subjectively defined ''semantic categories'' along with their weights of their categories, and this method was the most successful among other methods in the research for distinguishing all four pairs of dichotomies in MBTI.…”

Section: Feature Extraction Methods In Mbti Predictionmentioning

confidence: 99%

Predicting judging-perceiving of Myers-Briggs Type Indicator (MBTI) in online social forum

Choong

Varathan

2021

PeerJ

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The Myers-Briggs Type Indicator (MBTI) is a well-known personality test that assigns a personality type to a user by using four traits dichotomies. For many years, people have used MBTI as an instrument to develop self-awareness and to guide their personal decisions. Previous researches have good successes in predicting Extraversion-Introversion (E/I), Sensing-Intuition (S/N) and Thinking-Feeling (T/F) dichotomies from textual data but struggled to do so with Judging-Perceiving (J/P) dichotomy. J/P dichotomy in MBTI is a non-separable part of MBTI that have significant inference on human behavior, perception and decision towards their surroundings. It is an assessment on how someone interacts with the world when making decision. This research was set out to evaluate the performance of the individual features and classifiers for J/P dichotomy in personality computing. At the end, data leakage was found in dataset originating from the Personality Forum Café, which was used in recent researches. The results obtained from the previous research on this dataset were suggested to be overly optimistic. Using the same settings, this research managed to outperform previous researches. Five machine learning algorithms were compared, and LightGBM model was recommended for the task of predicting J/P dichotomy in MBTI personality computing.

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Section: Feature Extraction Methods In Mbti Predictionmentioning

confidence: 99%

Predicting judging-perceiving of Myers-Briggs Type Indicator (MBTI) in online social forum

Choong

Varathan

2021

PeerJ

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“…By performing lemmatization, inflected forms of the same word will represent a single node, rather than multiple nodes, in the graph [ 31 ]. Lemmatization can be implemented by means of natural language processing tools employing lexical databases such as WordNet [ 41 ] or the Stanford CoreNLP Natural Language Processing Toolkit [ 42 ] as reference. An alternative approach to lemmatization is stemming, which is the process of reducing inflected words to their ‘root’ (or ‘stem’) form.…”

Section: Graph Analysis: Exploring the Structural Properties Of Mentation Reportsmentioning

confidence: 99%

The Language of Dreams: Application of Linguistics-Based Approaches for the Automated Analysis of Dream Experiences

2021

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The study of dreams represents a crucial intersection between philosophical, psychological, neuroscientific, and clinical interests. Importantly, one of the main sources of insight into dreaming activity are the (oral or written) reports provided by dreamers upon awakening from their sleep. Classically, two main types of information are commonly extracted from dream reports: structural and semantic, content-related information. Extracted structural information is typically limited to the simple count of words or sentences in a report. Instead, content analysis usually relies on quantitative scores assigned by two or more (blind) human operators through the use of predefined coding systems. Within this review, we will show that methods borrowed from the field of linguistic analysis, such as graph analysis, dictionary-based content analysis, and distributional semantics approaches, could be used to complement and, in many cases, replace classical measures and scales for the quantitative structural and semantic assessment of dream reports. Importantly, these methods allow the direct (operator-independent) extraction of quantitative information from language data, hence enabling a fully objective and reproducible analysis of conscious experiences occurring during human sleep. Most importantly, these approaches can be partially or fully automatized and may thus be easily applied to the analysis of large datasets.

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“…The query was then enriched by a customised query expansion mechanism in which each term in the query would be mapped into specific words in the index based on its similarity scores. These scores were calculated by using Word2Vec model [28], and the synonyms, hypernyms, and hyponyms from WordNet [31]. These mapped terms were used to compute a ranked list of image surrogates using a novel scoring measurement called aTF-IDF [37], short for area term frequency-inverse document frequency, inspired from the original TF-IDF measure usually used in the information retrieval field.…”

Section: The Myscéal System 41 Myscéal System Operationmentioning

confidence: 99%

Myscéal 2.0: A Revised Experimental Interactive Lifelog Retrieval System for LSC'21

Tran

Nguyen

Bình

et al. 2021

Proceedings of the 4th Annual on Lifelog Search Challenge

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Building an interactive retrieval system for lifelogging contains many challenges due to massive multi-modal personal data besides the requirement of accuracy and rapid response for such a tool. The Lifelog Search Challenge (LSC) is the international lifelog retrieval competition that inspires researchers to develop their systems to cope with the challenges and evaluates the effectiveness of their solutions. In this paper, we upgrade our previous Myscéal and present Myscéal 2.0 system for the LSC'21 with the improved features inspired by the novice users experiments. The experiments show that a novice user achieved more than half of the expert score on average. To mitigate the gap of them, some potential enhancements were identified and integrated to the enhanced version. CCS CONCEPTS• Information systems → Information retrieval; • Humancentered computing → Human computer interaction (HCI); User interface design.

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WordNet: An electronic lexical database. Christiane Fellbaum (Ed.). Cambridge, MA: MIT Press, 1998. Pp. 423.

Cited by 25 publications

References 0 publications

Predicting judging-perceiving of Myers-Briggs Type Indicator (MBTI) in online social forum

Predicting judging-perceiving of Myers-Briggs Type Indicator (MBTI) in online social forum

The Language of Dreams: Application of Linguistics-Based Approaches for the Automated Analysis of Dream Experiences

Myscéal 2.0: A Revised Experimental Interactive Lifelog Retrieval System for LSC'21

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