The Impact of Concept Representation in Interactive Concept Validation (ICV)

Large scale ideation has developed as a promising new way of obtaining large numbers of highly diverse ideas for a given challenge. However, due to the scale of these challenges, algorithmic support based on a computational understanding of the ideas is a crucial component in these systems. One promising solution is the use of knowledge graphs to provide meaning. A significant obstacle lies in word-sense disambiguation, which cannot be solved by automatic approaches. In previous work, we introduce \textit{Interactive Concept Validation} (ICV) as an approach that enables ideators to disambiguate terms used in their ideas. To test the impact of different ways of representing concepts (should we show images of concepts, or only explanatory texts), we conducted experiments comparing three representations. The results show that while the impact on ideation metrics was marginal, time/click effort was lowest in the images only condition, while data quality was highest in the both condition

The Role of Definitions in Biomedical Concept Representation

The Foundational Model (FM) of anatomy, developed as an anatomical enhancement of UMLS, classifies anatomical entities in a structural context. Explicit definitions have played a critical role in the establishment of FM classes. Essential structural properties that distinguish a group of anatomical entities serve as the differentiae for defining classes. These, as well as other structural attributes, are introduced as template slots in Protege, a frame-based knowledge acquisition system, and are inherited by descendants of the class. A set of desiderata has evolved during the instantiation of the FM for formulating definitions. We contend that 1. these desiderata generalize to non-anatomical domains and 2. satisfying them in constituent vocabularies of UMLS would enhance the quality of information retrievable through UMLS

The Schwinger Representation of a Group: Concept and Applications

The concept of the Schwinger Representation of a finite or compact simple Lie group is set up as a multiplicity-free direct sum of all the unitary irreducible representations of the group. This is abstracted from the properties of the Schwinger oscillator construction for SU(2), and its relevance in several quantum mechanical contexts is highlighted. The Schwinger representations for $SU(2), SO(3)$ and SU(n) for all $n$ are constructed via specific carrier spaces and group actions. In the SU(2) case connections to the oscillator construction and to Majorana's theorem on pure states for any spin are worked out. The role of the Schwinger Representation in setting up the Wigner-Weyl isomorphism for quantum mechanics on a compact simple Lie group is brought out.Comment: Latex, 17 page

A Unified multilingual semantic representation of concepts

Semantic representation lies at the core of several applications in Natural Language Processing. However, most existing semantic representation techniques cannot be used effectively for the representation of individual word senses. We put forward a novel multilingual concept representation, called MUFFIN , which not only enables accurate representation of word senses in different languages, but also provides multiple advantages over existing approaches. MUFFIN represents a given concept in a unified semantic space irrespective of the language of interest, enabling cross-lingual comparison of different concepts. We evaluate our approach in two different evaluation benchmarks, semantic similarity and Word Sense Disambiguation, reporting state-of-the-art performance on several standard datasets

Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network

Language in social media is extremely dynamic: new words emerge, trend and disappear, while the meaning of existing words can fluctuate over time. Such dynamics are especially notable during a period of crisis. This work addresses several important tasks of measuring, visualizing and predicting short term text representation shift, i.e. the change in a word's contextual semantics, and contrasting such shift with surface level word dynamics, or concept drift, observed in social media streams. Unlike previous approaches on learning word representations from text, we study the relationship between short-term concept drift and representation shift on a large social media corpus - VKontakte posts in Russian collected during the Russia-Ukraine crisis in 2014-2015. Our novel contributions include quantitative and qualitative approaches to (1) measure short-term representation shift and contrast it with surface level concept drift; (2) build predictive models to forecast short-term shifts in meaning from previous meaning as well as from concept drift; and (3) visualize short-term representation shift for example keywords to demonstrate the practical use of our approach to discover and track meaning of newly emerging terms in social media. We show that short-term representation shift can be accurately predicted up to several weeks in advance. Our unique approach to modeling and visualizing word representation shifts in social media can be used to explore and characterize specific aspects of the streaming corpus during crisis events and potentially improve other downstream classification tasks including real-time event detection

Defending the Structural Concept of Representation

The aim of this paper is to defend the structural concept of representation, as defined by homomorphisms, against its main objections, namely: logical objections, the objection from misrepresentation, the objection from failing necessity, and the copy theory objection. The logical objections can be met by reserving the relation ¿to be homomorphic to¿ for the explication of potential representation (or, of the representational content). Actual reference objects (¿targets¿) of representations are determined by (intentional or causal) representational mechanisms. Appealing to the independence of the dimensions of ¿content¿ and ¿target¿ also helps to see how the structural concept can cope with misrepresentation. Finally, I argue that homomorphic representations are not necessarily ¿copies¿ of their representanda, and thus can convey scientific insight