کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
424795 685642 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Binary sieves: Toward a semantic approach to user segmentation for behavioral targeting
ترجمه فارسی عنوان
غربال باینری: به سوی رویکرد معناشناختی به تقسیم بندی کاربر برای هدفگیری رفتاری
کلمات کلیدی
تقسیم کاربر؛ تجزیه و تحلیل معنایی؛ هدف گیری رفتاری
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی


• We propose a novel segmentation approach for user targeting, based on a semantic analysis of the items evaluated by a user.
• Through the semantic analysis we extend the ground truth, to generate non trivial segments.
• With respect to classic segmentation, the advertiser can introduce constraints and atomically model the user segments.

Behavioral targeting is the process of addressing ads to a specific set of users. The set of target users is detected from a segmentation of the user set, based on their interactions with the website (pages visited, items purchased, etc.). Recently, in order to improve the segmentation process, the semantics behind the user behavior has been exploited, by analyzing the queries issued by the users. However, nearly half of the times users need to reformulate their queries in order to satisfy their information need. In this paper, we tackle the problem of semantic behavioral targeting considering reliable user preferences, by performing a semantic analysis on the descriptions of the items positively rated by the users. We also consider widely-known problems, such as the interpretability of a segment, and the fact that user preferences are usually stable over time, which could lead to a trivial segmentation. In order to overcome these issues, our approach allows an advertiser to automatically extract a user segment by specifying the interests that she/he wants to target, by means of a novel boolean algebra; the segments are composed of users whose evaluated items are semantically related to these interests. This leads to interpretable and non-trivial segments, built by using reliable information. Experimental results confirm the effectiveness of our approach at producing users segments.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Future Generation Computer Systems - Volume 64, November 2016, Pages 186–197
نویسندگان
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