An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

Etsy is a global marketplace where people across the world connect to make, buy and sell unique goods. Sellers at Etsy can promote their product listings via advertising campaigns similar to traditional sponsored search ads. Click-Through Rate (CTR) prediction is an integral part of online search advertising systems where it is utilized as an input to auctions which determine the final ranking of promoted listings to a particular user for each query. In this paper, we provide a holistic view of Etsy's promoted listings' CTR prediction system and propose an ensemble learning approach which is based on historical or behavioral signals for older listings as well as content-based features for new listings. We obtain representations from texts and images by utilizing state-of-the-art deep learning techniques and employ multimodal learning to combine these different signals. We compare the system to non-trivial baselines on a large-scale real world dataset from Etsy, demonstrating the effectiveness of the model and strong correlations between offline experiments and online performance. The paper is also the first technical overview to this kind of product in e-commerce context

Reviews

Web‐Teaching ‐ A Guide to Interactive Teaching for the World‐Wide Web by David W. Brooks, New York: Plenum, 1997. ISBN: 0–306–45552–8. Paperback, 214 pages. $30

Adapting to trauma: disengagement as a holding strategy

Purpose – The purpose of this paper is to draw upon a range of material to improve the understanding of disengagement with everyday life, by some individuals who have learning disabilities and mental health difficulties. Illustrative incidents from historical clinical cases are utilised, to consider whether this reframing may enhance the interpretation of presenting behaviours. Design/methodology/approach – Key recurring themes within transpersonal literature were reviewed, relevant to adults with behaviour indicating a degree of disengagement from everyday life. These were grouped into Physical Realm, Psychosocial Realm and Realm of Being. Illustrative examples of behaviour are reviewed and re-interpreted within this framework. Findings – These examples generated plausible interpretations for the presenting behaviours within this framework of the Three Realms. These interpretations support a fresh understanding of the quality of the individual’s inner experience. This paper suggests a potential framework to consider the way in which some individuals may experience a different quality of consciousness than the usual. Practical implications – Use of the Three Realms for behaviour interpretation should result into a more empathetic and client-centred approach that could reduce the need for aversive approaches, lessening risk for the client and any employing organisation. The identification of behaviours that signal participation in the Realm of Being could be defined and evaluated with the potential to be used to inform the nature and content of the support provided. Originality/value – This paper, rooted in clinical examples, offers an original synthesis with reasons to include the immaterial realm in the perspective of the human condition. This could benefit people with substantial episodes of disconnection from the Physical Realm and everyday culture and those who support them

Why Youth (heart) Social Network Sites: The Role of Networked Publics in Teenage Social Life

Part of the Volume on Youth, Identity, and Digital Media Social network sites like MySpace and Facebook serve as "networked publics." As with unmediated publics like parks and malls, youth use networked publics to gather, socialize with their peers, and make sense of and help build the culture around them. This article examines American youth engagement in networked publics and considers how properties unique to such mediated environments (e.g., persistence, searchability, replicability, and invisible audiences) affect the ways in which youth interact with one another. Ethnographic data is used to analyze how youth recognize these structural properties and find innovative ways of making these systems serve their purposes. Issues like privacy and impression management are explored through the practices of teens and youth participation in social network sites is situated in a historical discussion of youth's freedom and mobility in the United States

The use of project case histories to assess undergraduate students' understanding of professional practice issues within architecture

This case study documents and reflects on the experience of introducing a practice-based assignment into the professional practice curriculum that enabled third year Architecture students at Strathclyde University to deepen their understanding of practice through the development of project case histories. It outlines the issues involved including the benefits which may be gained and the problems encountered in the process of assessment

What your Facebook Profile Picture Reveals about your Personality

People spend considerable effort managing the impressions they give others. Social psychologists have shown that people manage these impressions differently depending upon their personality. Facebook and other social media provide a new forum for this fundamental process; hence, understanding people's behaviour on social media could provide interesting insights on their personality. In this paper we investigate automatic personality recognition from Facebook profile pictures. We analyze the effectiveness of four families of visual features and we discuss some human interpretable patterns that explain the personality traits of the individuals. For example, extroverts and agreeable individuals tend to have warm colored pictures and to exhibit many faces in their portraits, mirroring their inclination to socialize; while neurotic ones have a prevalence of pictures of indoor places. Then, we propose a classification approach to automatically recognize personality traits from these visual features. Finally, we compare the performance of our classification approach to the one obtained by human raters and we show that computer-based classifications are significantly more accurate than averaged human-based classifications for Extraversion and Neuroticism

Design of teaching materials informed by consideration of learning-impaired students

The general aim of this project is to fundamentally re-think the design of teaching materials in view of what is now known about cognitive deficits and about what Howard Gardner has termed ‘multiple intelligences’. The applicant has implemented this strategy in two distinct areas, the first involving the writing of an English language programme for Chinese speakers, the second involving the construction of specialized equipment for teaching elementary logic to blind students. The next phase (for which funding is sought) is to test the effectiveness of the logic device, because in theory – the one to be tested – materials the design of which is informed by the above rationale will provide a richer learning experience for non-impaired users

Intelligent Word Embeddings of Free-Text Radiology Reports

Radiology reports are a rich resource for advancing deep learning applications in medicine by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the ambiguity and subtlety of natural language. We propose a hybrid strategy that combines semantic-dictionary mapping and word2vec modeling for creating dense vector embeddings of free-text radiology reports. Our method leverages the benefits of both semantic-dictionary mapping as well as unsupervised learning. Using the vector representation, we automatically classify the radiology reports into three classes denoting confidence in the diagnosis of intracranial hemorrhage by the interpreting radiologist. We performed experiments with varying hyperparameter settings of the word embeddings and a range of different classifiers. Best performance achieved was a weighted precision of 88% and weighted recall of 90%. Our work offers the potential to leverage unstructured electronic health record data by allowing direct analysis of narrative clinical notes.Comment: AMIA Annual Symposium 201