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GrammAds : Keyword and Ad Creative Generator for Online Advertising Campaigns. Author : Stamatina Thomaidou , Konstantinos Leymonis , and Michalis Vazirgiannis Presenter: Wayne Yang. A genda. Introduction Related Work Keyword Generation Ad Creative Generation
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GrammAds: Keyword and Ad Creative Generator for Online Advertising Campaigns Author:StamatinaThomaidou, KonstantinosLeymonis, and MichalisVazirgiannis Presenter:WayneYang
Agenda • Introduction • Related Work • KeywordGeneration • AdCreativeGeneration • CampaignOrganizationandUseCases • System Architecture and Communication • Experimental Evaluation • Conclusionandfuturework
Introduction-Baseline Campaign Creation Process Product Alandingwebpage (price, buy) Advertising text Findingkeyword
Introduction-Motivation for an Automated Application • An advertiser decides • Usuallychoosespecific1-3keywordsperproduct • Shortheadlineandadtext • maximum cost-per-click of each keyword =>effective keyword selection is one of the most important success factors for online advertising
RelatedWork • GoogleAdwords-They start from an ini- tial key phrase and they are based on past queries that contain these search terms. • Other commercial tools-determine an advertiser’s top competitors and then actively search for the keywords they are targeting. • TermsNet and Wordy-With their methods they find other semantically similar terms.
Keyword Generation • Keyword Extraction • Landingpageparsed=> stopwordsremoved => trigram, bigrams,unigram=>calculaterelevancekeyword • Keyword Suggestion • Seedkeywords=>top30resultpages=>corpus=>lucenescore
AdCreativeGeneration • generic summary-shows the main topics and key contents covered in the source text • query-relevant summary-locates the contentspertinent to user’s seeking goals(oursystemprovided) • extracttext=>Bayesianclassifiertosummarize
CampaignOrganizationandUseCases • Step1–initialsettings • 1.nooptimization-wherethesystemjustuploadsautomaticallythegeneratedkeywords, ad-texts, and bids along with their organized structure without continuing to be responsible for an automated optimization strategy • 2.trafficoptimization-where the advertiser considers the profit to be the amount of clicks at the ad-texts • 3.profitoptimization-where the profit is the actual monetary profit from offline product sales or online conversions to a specific landing page that is defined in a next step • Step2–Crawlermodule • Step3–selectkeyword
CampaignOrganizationandUseCases • Step4-Automatically generated keywords and recommended bids • Step5-the user can see through the GoogleAdWordsinterface the uploaded settings of his constructed campaign.
System Architecture and Communication • The proposed system structure resulted as a need for an appropriate user inter- face interaction of the Adomaton subsystem, which optimizes Google AdWords Campaigns through a novel bidding strategy. • Adoptmodelviewcontroller forinformationmanagment
Conclusionandfuturework • Automating the task of finding the appropriate keywords • Recommending multiword terms (n-grams) with high specificity without the need to capitalize on usage data such as query and web traffic logs • Generating fast snippets of ad texts • An automated and fast way of uploading campaign and AdGroup settings (keywords and ad-texts per AdGroup) into the AdWords service • A developed web application with an initial experimentation on real world campaigns