کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969587 1449974 2018 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
User attribute discovery with missing labels
ترجمه فارسی عنوان
کشف کاربر با برچسب های گم شده
کلمات کلیدی
خصیصه کاربر، سنسور هوشمند یادگیری چند کاره یادگیری نیمه نظارتی، برچسبهای گمشده، رتبه پایین
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


- We propose a new problem, i.e., user attribute discovery via smart sensor data.
- We design a new a semi-supervised multi-task learning model (S2MTL) for user attribute discovery with missing label.
- To reduce the model complexity of high-dimensional data, we learn the mapping feature dictionary and attribute space information simultaneously.
- We also build a new smart building dataset.

In this paper, we focus on user attribute analysis by recasting such a problem as a multi-task learning issue, where each attribute is considered as an independent task. In comparison with traditional data analysis, the missing labels problem broadly presents for smart sensor data due to some objective / subjective factors, where the label incompleteness increases the difficulty significantly. Therefore, we design a semi-supervised multi-task learning model (S2MTL) to handle the missing labels issue. For modeling, we integrate the matrix factorization to learn the mapping feature dictionary and attribute space information simultaneously, and adopt the pairwise affinity similarity to incorporate the unlabeled data information, where the low rank property and model efficiency can be well controlled. For model optimization, we convert our model as two individual convex subproblems with one non-smooth, and implement an alternating direction method to generate an efficient optimal solution. State-of-the-art models have validated the effectiveness and efficiency of our proposed model via extensive experiments and comparisons, on two public datasets and our new smart building dataset.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 73, January 2018, Pages 33-46
نویسندگان
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