Dr Victoria Yaneva recently attended the 15th Web for All Conference and presented the co-authored paper ‘Detecting Autism Based on Eye-Tracking Data from Web Searching Tasks’. The paper was awarded the Best Technical Paper – we would like to congratulate Dr Yaneva and her co-authors Dr Le An Ha, Dr Sukru, Dr Yeliz Yesilada and Professor Mitkov.
The Research Group in Computational Linguistics at the University of Wolverhampton (http://rgcl.wlv.ac.uk) is currently recruiting a Lecturer/Senior Lecturer in Translation Technology (permanent). The purpose of this post is to strengthen the research group by enhancing its research and publications in the field of translation technology. The appointed candidate will be expected to produce REF-returnable outputs, attract external income, seek industrial collaborations, teach at Masters level and supervise PhD students. He/she will join a recently appointed research fellow and two PhD students in translation technology. All these posts are part of a university investment in the area of translation technology.
The Research Group in Computational Linguistics invites applications for TWO 3-year PhD studentships in the area of translation technology. These two PhD studentships are part of a larger university investment which includes other PhD students and members of staff with the aim to strengthen the existing research undertaken by members of the group in this area. These funded student bursaries consist of a stipend towards living expenses (£14,500 per year) and remission of fees.
The area of Natural Language Engineering, and Natural Language Processing in general, is following the trend of many other areas in becoming highly specialised, with a number of application-orientated and narrow-domain topics emerging or growing in importance. These developments, often coinciding with a lack of related literature, necessitate and warrant the publication of specialised volumes focusing on a specific topic of interest to the Natural Language Processing (NLP) research community.
The Journal of Natural Language Engineering (JNLE), which now features six 160-page issues per year and has increased its impact factor for third consecutive year, invites proposals for special issues on a competitive basis regarding any topics surrounding applied NLP which have emerged as important recent developments and that have attracted the attention of a number of researchers or research groups. In recent years, Calls for Proposals for special issues have resulted in high-quality outputs and this year we look forward to another successful competition.
Last week, the RGCL and SCRG PhD Students presented their research to their peers and staff members from across the University. The posters were well received.
Statistical Cybermetrics Research Group
David Foster: ‘Determining YouTube Video Popularity: Analysing YouTube User Behaviours’
Kuk Aduku: ‘ Do Patents Cite Conference Papers as Often as Journal Articles in Engineering? An Investigation of Four Fields’
Research Group in Computational Linguistics
Mohammad Alharbu: ‘Readability Assessment for Arabic as a Second Language’
Najah Albaqawi: ‘Gender Variation in Gulf Pidgin Arabic’
This poster is an attempt to provide a quantitative variationist analysis on variability in GPA morpho-syntax (Arabic definiteness markers, Arabic conjunction markers, object or possessive pronoun, GPA copula, and agreement in the verb phrase and the noun phrase) which aims to discover the potential effect of the three factors: male and female gender, speakers’ first language, and number of years spent in the Gulf.
Richard Evans: ‘Sentence Rewriting for Language Processing’
This poster provided an overview of the OB1 sentence simplification system. In this approach, the functions of various textual markers of syntactic complexity (conjunctions, relative pronouns, and punctuation marks) are identified and used to inform an iterative rule-based sentence transformation process.
Ahmed Omer: ‘New Techniques For Finding Authorship in Arabic Texts’
The degree of stylistic difference between a pair of documents can then be found by any of a number of measures which compare the sets of linguistic features for each document. In general, The technique is used to first find a set of linguistic features and a difference measure which successfully discriminates between texts known to be either by author A or author B. Then texts of unknown authorship are compared against these texts to see whether their writing style is more similar to author A or author B.
Omid Rohanian: ‘ NLP Approaches to estimating Text Difficulty’
I am exploring NLP approaches in investigating text difficulty at the level of concepts.
Shiva Taslimpoor: ‘Automatic Extraction and Translation of Multiword Expressions’
We employ the state-of-the-art word embedding approaches to automatically identify and translate idiosyncratic Multiword Expressions.