Evaluating Tag-Based Preference Obfuscation Systems

Evaluating Preference-Based Feedback in Recommender Systems

Evaluating Safety, Soundness and Sensibleness of Obfuscation Systems

Author masking is the task of paraphrasing a document so that its writing style no longer matches that of its original author. This task was introduced as part of the 2016 PAN Lab on Digital Text Forensics, for which a total of three research teams submitted their results. This work describes our methodology to evaluate the submitted obfuscation systems based on their safety, soundness and sens...

Predicting Users' Preference from Tag Relevance

Tagging has become a powerful means for users to find, organize, understand and express their ideas about online entities. However, tags present great challenges when researchers try to incorporate them into the prediction task of recommender systems. In this paper, we propose a novel approach to infer user preference from tag relevance, an indication of how strong each tag applies to each item...

Goal-Based Qualitative Preference Systems

Goals are not only used to identify desired states or outcomes, but may also be used to derive qualitative preferences between outcomes. We show that Qualitative Preference Systems (QPSs) provide a general, flexible and succinct way to represent preferences based on goals. If the domain is not Boolean, preferences are often based on orderings on the possible values of variables. We show that QP...

P systems based on tag operations

In this article we introduce P systems using Post’s tag operation on strings. We show that the computational completeness can be achieved even if the deletion length is equal to one.