Dynamic contextualized word embeddings
Static word embeddings that represent words by a single vector cannot capture the
variability of word meaning in different linguistic and extralinguistic contexts. Building on …
variability of word meaning in different linguistic and extralinguistic contexts. Building on …
Employing personal word embeddings for personalized search
Personalized search is a task to tailor the general document ranking list based on user
interests to better satisfy the user's information need. Many personalized search models …
interests to better satisfy the user's information need. Many personalized search models …
A comparative study on linguistic theories for modeling EFL learners: facilitating personalized vocabulary learning via task recommendations
Personalized learning has become an important and powerful paradigm catering for various
needs, styles, preferences, and modes of learning. Several methods including task …
needs, styles, preferences, and modes of learning. Several methods including task …
Language as a fingerprint: Self-supervised learning of user encodings using transformers
The way we talk carries information about who we are. Demographics, personality, clinical
conditions, political preferences influence what we speak about and how, suggesting that …
conditions, political preferences influence what we speak about and how, suggesting that …
Building user-oriented personalized machine translator based on user-generated textual content
Machine Translation (MT) has been a very useful tool to assist multilingual communication
and collaboration. In recent years, by taking advantage of the exciting developments of …
and collaboration. In recent years, by taking advantage of the exciting developments of …
Clarifying ambiguous keywords with personal word embeddings for personalized search
Personalized search tailors document ranking lists for each individual user based on her
interests and query intent to better satisfy the user's information need. Many personalized …
interests and query intent to better satisfy the user's information need. Many personalized …
PerPLM: Personalized Fine-tuning of Pretrained Language Models via Writer-specific Intermediate Learning and Prompts
The meanings of words and phrases depend not only on where they are used (contexts) but
also on who use them (writers). Pretrained language models (PLMs) are powerful tools for …
also on who use them (writers). Pretrained language models (PLMs) are powerful tools for …
User factor adaptation for user embedding via multitask learning
Language varies across users and their interested fields in social media data: words
authored by a user across his/her interests may have different meanings (eg, cool) or …
authored by a user across his/her interests may have different meanings (eg, cool) or …
User Persona Identification and New Service Adaptation Recommendation
Providing a personalized user experience on information dense webpages helps users in
reaching their end-goals sooner. We explore an automated approach to identifying user …
reaching their end-goals sooner. We explore an automated approach to identifying user …
[图书][B] Linguistic variation in online communities: A computational perspective
M Del Tredici - 2020 - pure.uva.nl
This work is based on a very simple observation: The meaning of a word is a dynamic object
that greatly varies depending on the individuals who use that word and when the word is …
that greatly varies depending on the individuals who use that word and when the word is …