Domain adaptation for statistical machine translation of corporate and user-generated content

The growing popularity of Statistical Machine Translation (SMT) techniques in recent years has led to the development of multiple domain-specic resources and adaptation scenarios. In this thesis we address two important and industrially relevant adaptation scenarios, each suited to different kinds of content. Initially focussing on professionally edited `enterprise-quality' corporate content, we address a specic scenario of data translation from a mixture of different domains where, for each of them domain-specific data is available. We utilise an automatic classifier to combine multiple domain-specific models and empirically show that such a configuration results in better translation quality compared to both traditional and state-of-the-art techniques for handling mixed domain translation. In the second phase of our research we shift our focus to the translation of possibly `noisy' user-generated content in web-forums created around products and services of a multinational company. Using professionally edited translation memory (TM) data for training, we use different normalisation and data selection techniques to adapt SMT models to noisy forum content. In this scenario, we also study the effect of mixture adaptation using a combination of in-domain and out-of-domain data at different component levels of an SMT system. Finally we focus on the task of optimal supplementary training data selection from out-of-domain corpora using a novel incremental model merging mechanism to adapt TM-based models to improve forum-content translation quality

Finding a Way Out of the Ethnographic Paradigm Jungle

In this paper, an attempt has been made to develop a hybrid ethnographic paradigm, taking the best points from the different approaches of ethnographic research. The pioneering proponents of ethnography differed in their conceptualization of the method, resulting in the development of three distinct schools of thought-holistic, semiotic and behavioristic. These three ethnographic paradigms have their respective benefits and shortcomings. Following any one of these approaches may lead to only partial comprehension of the phenomenon by the ethnographer. This study wished to address this issue by developing a best practice approach, which will have the virtues of all the three paradigms. It is hoped that this evolved paradigm will help in making the work of the ethnographer a lot more comprehensive and the experience much richer

Role Stress and Coping Among Business School Professors: A Phenomenological Study

The purpose of the paper is to identify the determinants of role stress amongst business school professors in India and explore the coping strategies followed by them based on the professional experiences shared by the professors. We employ Interpretative Phenomenological Analysis (IPA) to gain insights into the causes of rising levels of stress in business schools and the practised coping strategies from the professors’ perspective based on their narratives of lived experiences. We conducted semi-structured interviews with 64 professors from 29 public and private business schools in India. Analysis of qualitative data resulted in the emergence of 11 themes; we make recommendations based on the themes for the business schools’ management to assist the professors in alleviating role stress. As pointed out by Chong and Ahmed (2014), phenomenological studies are rarely used for inquiry in the higher education context. The insights gathered from IPA help in understanding the tenacious causes of role stress in the management institutes and the day-to-day coping strategies followed to reduce the same

A Key Challenge in Global HRM: Adding New Insights to Existing Expatriate Spouse Adjustment Models

This study is an attempt to strengthen the existing knowledge about factors affecting the adjustment process of the trailing expatriate spouse and the subsequent impact of any maladjustment or expatriate failure. We conducted a qualitative enquiry using grounded theory methodology with 26 Indian spouses who had to deal with their partner’s expatriate assignment relocation. The open and axial coding techniques and the process of theoretical sampling are discussed at length. Our investigation reveals the recurrence of several factors earlier studied in previous models such as cultural novelty, family and peer support, the organization’s support and the spouse’s personality. Additionally, we found that the Indian spouses’ adjustment to expatriate assignments was influenced greatly by their perceived gender-role ideology and their marital obligations to their partners. The resulting extended model of spousal adjustment to expatriate adjustments may help management practitioners to enhance expatriate success in global assignments

A Content Analysis of the Leadership Styles of Steve Waugh and Sourav Ganguly: Leadership Lesson from the Game of Cricket

In this study, the researchers focus on the leadership styles of two of the game of Cricket’s most charismatic leaders of the twenty-first century – Steve Waugh of Australia and Sourav Ganguly of India in a bid to relate their styles with classic leadership theories. Both Waugh and Ganguly have been arguably recognized as the most successful cricket captains of their respective countries and have earned accolades from cricket pundits as brilliant leaders of men. In this study, a content analysis of the articles about these two legendary captains published in the highly-acclaimed Wisden almanac, electronic media such as Sportstar, Cricinfo Magazine and standard newspapers of India, Australia and other neutral countries was undertaken. The content analysis of eighty-seven articles spreading over a page length of 127 A-4 size papers revealed Waugh to be a more result-driven autocratic leader who led more by example, while Ganguly showed traits of a transformational leader who led by motivating his teammates. The study is expected to contribute to the existing body of leadership research with some new knowledge of the construct of leadership, which have been discussed at length in this paper

Combining multi-domain statistical machine translation models using automatic classifiers

This paper presents a set of experiments on Domain Adaptation of Statistical Machine Translation systems. The experiments focus on Chinese-English and two domain-specific corpora. The paper presents a novel approach for combining multiple domain-trained translation models to achieve improved translation quality for both domain-specific as well as combined sets of sentences. We train a statistical classifier to classify sentences according to the appropriate domain and utilize the corresponding domain-specific MT models to translate them. Experimental results show that the method achieves a statistically significant absolute improvement of 1.58 BLEU (2.86% relative improvement) score over a translation model trained on combined data, and considerable improvements over a model using multiple decoding paths of the Moses decoder, for the combined domain test set. Furthermore, even for domain-specific test sets, our approach works almost as well as dedicated domain-specific models and perfect classification

MATREX: the DCU MT system for WMT 2010

This paper describes the DCU machine translation system in the evaluation campaign of the Joint Fifth Workshop on Statistical Machine Translation and Metrics in ACL-2010. We describe the modular design of our multi-engine machine translation (MT) system with particular focus on the components used in this participation. We participated in the English–Spanish and English–Czech translation tasks, in which we employed our multiengine architecture to translate. We also participated in the system combination task which was carried out by the MBR decoder and confusion network decoder

Domain adaptation for statistical machine translation of corporate and user-generated content

The growing popularity of Statistical Machine Translation (SMT) techniques in recent years has led to the development of multiple domain-specic resources and adaptation scenarios. In this thesis we address two important and industrially relevant adaptation scenarios, each suited to different kinds of content. Initially focussing on professionally edited `enterprise-quality\u27 corporate content, we address a specic scenario of data translation from a mixture of different domains where, for each of them domain-specific data is available. We utilise an automatic classifier to combine multiple domain-specific models and empirically show that such a configuration results in better translation quality compared to both traditional and state-of-the-art techniques for handling mixed domain translation. In the second phase of our research we shift our focus to the translation of possibly `noisy\u27 user-generated content in web-forums created around products and services of a multinational company. Using professionally edited translation memory (TM) data for training, we use different normalisation and data selection techniques to adapt SMT models to noisy forum content. In this scenario, we also study the effect of mixture adaptation using a combination of in-domain and out-of-domain data at different component levels of an SMT system. Finally we focus on the task of optimal supplementary training data selection from out-of-domain corpora using a novel incremental model merging mechanism to adapt TM-based models to improve forum-content translation quality

Talent Attraction through Online Recruitment Websites: Application of Web 2.0 Technologies

Talent attraction is one of the major challenges for HR managers. With the rise of online recruitment channels, the number of applicants for a given job vacancy have increased substantially. In addition, the time taken in finding the right talent from the huge pool of applications has increased significantly, adding up to the hiring cycle. In today’s competitive labour market, employers need to highlight their brand image to prospective job-seekers, so that there is higher chance of recruiting the best talent that fits their manpower requirement. In this paper, an attempt is made in investigating that to what extent web 2.0 technologies such as podcasts, blogs and online employee testimonials may enhance the employer's brand value in the eyes of employed professionals. A multi-group moderated mediation analysis is conducted with 361 working professionals who are active online recruitment platform users. The analysis helps establish the effect of the perceived quality and credibility of career websites on job-seekers’ perception about the employer and on their subsequent application intention. The findings reveal positive effect of video podcasts and realistic employee testimonials presented through third party blogs on job-seekers’ perceived quality and credibility of the job advertisement. This phenomenon is reflected in their heightened attraction for the employer and eventual intention to apply for jobs at the firm

Antecedents of organisational creativity: a multi-level approach

The purpose of this literature review is to provide a better understanding of the antecedents of organisational creativity with a multi-level approach. Organisational creativity is a sum total of the creativity accounted for by the individual employees of the organisation, the cumulative creativity of a team or group and creativity arising out of different structural components of an organisation. Some of the antecedents identified from the literature include personality, intrinsic motivation, group cohesion, social inhibition, cognitive interference, leader member exchange, organisational culture and climate, amongst others at individual, group and organisational level. Based on the literature review, suggestions for future research and research propositions have been proposed