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Automated snippet generation for online advertising

Published: 27 October 2013 Publication History

Abstract

Products, services or brands can be advertised alongside the search results in major search engines, while recently smaller displays on devices like tablets and smartphones have imposed the need for smaller ad texts. In this paper, we propose a method that produces in an automated manner compact text ads (promotional text snippets), given as input a product description webpage (landing page). The challenge is to produce a small comprehensive ad while maintaining at the same time relevance, clarity, and attractiveness. Our method includes the following phases. Initially, it extracts relevant and important n-grams (keywords) given the landing page. The keywords reserved must have a positive meaning in order to have a call-to-action style, thus we attempt sentiment analysis on them. Next, we build an Advertising Language Model to evaluate phrases in terms of their marketing appeal. We experiment with two variations of our method and we show that they outperform all the baseline approaches.

References

[1]
K. Bartz, C. Barr, and A. Aijaz. Natural language generation for sponsored-search advertisements. EC'08.
[2]
A. Z. Broder, E. Gabrilovich, V. Josifovski, G. Mavromatis, and A. J. Smola. Bid generation for advanced match in sponsored search. WSDM'11.
[3]
A. Fujita, K. Ikushima, S. Sato, R. Kamite, K. Ishiyama, and O. Tamachi. Automatic generation of listing ads by reusing promotional texts. ICEC'10.
[4]
E. Gabrilovich. Ad retrieval systems in vitro and in vivo: Knowledge-based approaches to computational advertising. ECIR'11.
[5]
K. Ganesan, C. Zhai, and E. Viegas. Micropinion generation: an unsupervised approach to generating ultra-concise summaries of opinions. WWW'12.
[6]
S. Ravi, A. Z. Broder, E. Gabrilovich, V. Josifovski, S. Pandey, and B. Pang. Automatic generation of bid phrases for online advertising. WSDM'10.

Cited By

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  • (2024)ATS: Auto Text Summarization using Natural Language Processing2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)10.1109/SCEECS61402.2024.10482227(1-5)Online publication date: 24-Feb-2024
  • (2024)When large language models meet personalization: perspectives of challenges and opportunitiesWorld Wide Web10.1007/s11280-024-01276-127:4Online publication date: 28-Jun-2024
  • (2022)Self-Supervised Augmentation and Generation for Multi-lingual Text Advertisements at BingProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539091(3187-3196)Online publication date: 14-Aug-2022
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  1. Automated snippet generation for online advertising

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    cover image ACM Conferences
    CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management
    October 2013
    2612 pages
    ISBN:9781450322638
    DOI:10.1145/2505515
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 27 October 2013

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    Author Tags

    1. automated ad-text generation
    2. online advertising
    3. sponsored search
    4. textual advertising

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    CIKM'13
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    CIKM'13: 22nd ACM International Conference on Information and Knowledge Management
    October 27 - November 1, 2013
    California, San Francisco, USA

    Acceptance Rates

    CIKM '13 Paper Acceptance Rate 143 of 848 submissions, 17%;
    Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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    Cited By

    View all
    • (2024)ATS: Auto Text Summarization using Natural Language Processing2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)10.1109/SCEECS61402.2024.10482227(1-5)Online publication date: 24-Feb-2024
    • (2024)When large language models meet personalization: perspectives of challenges and opportunitiesWorld Wide Web10.1007/s11280-024-01276-127:4Online publication date: 28-Jun-2024
    • (2022)Self-Supervised Augmentation and Generation for Multi-lingual Text Advertisements at BingProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539091(3187-3196)Online publication date: 14-Aug-2022
    • (2022)Urdu and Hindi Poetry Generation Using Neural NetworksData Management, Analytics and Innovation10.1007/978-981-19-2600-6_34(485-497)Online publication date: 22-Sep-2022
    • (2022)Generating Search Text Ads from Keywords and Landing Pages via BERT2BERTAdvances in Artificial Intelligence10.1007/978-3-030-96451-1_3(27-33)Online publication date: 26-Feb-2022
    • (2021)Text Summarization Techniques Using Natural Language Processing: A Systematic Literature ReviewVFAST Transactions on Software Engineering10.21015/vtse.v9i4.8569:4(102-108)Online publication date: 31-Dec-2021
    • (2021)Reinforcing Pretrained Models for Generating Attractive Text AdvertisementsProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining10.1145/3447548.3467105(3697-3707)Online publication date: 14-Aug-2021
    • (2021)Story Generation from Images Using Deep LearningInformation, Communication and Computing Technology10.1007/978-3-030-88378-2_16(198-208)Online publication date: 8-Oct-2021
    • (2021)SILVER: Generating Persuasive Chinese Product PitchAdvances in Knowledge Discovery and Data Mining10.1007/978-3-030-75765-6_52(652-663)Online publication date: 11-May-2021
    • (2020)A Review: Abstractive Text Summarization Techniques using NLP2020 International Conference on Advances in Computing, Communication & Materials (ICACCM)10.1109/ICACCM50413.2020.9213079(23-28)Online publication date: 21-Aug-2020
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