Reacting to Variations in Product Demand: An Application for Conversion\n Rate (CR) Prediction in Sponsored Search Article Swipe
Marcelo Tallis
,
Pranjul Yadav
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1806.08211
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1806.08211
In online internet advertising, machine learning models are widely used to\ncompute the likelihood of a user engaging with product related advertisements.\nHowever, the performance of traditional machine learning models is often\nimpacted due to variations in user and advertiser behavior. For example, search\nengine traffic for florists usually tends to peak around Valentine's day,\nMother's day, etc. To overcome, this challenge, in this manuscript we propose\nthree models which are able to incorporate the effects arising due to\nvariations in product demand. The proposed models are a combination of product\ndemand features, specialized data sampling methodologies and ensemble\ntechniques. We demonstrate the performance of our proposed models on datasets\nobtained from a real-world setting. Our results show that the proposed models\nmore accurately predict the outcome of users interactions with product related\nadvertisements while simultaneously being robust to fluctuations in user and\nadvertiser behaviors.\n
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Metadata
- Type
- preprint
- Landing Page
- http://arxiv.org/abs/1806.08211
- https://arxiv.org/pdf/1806.08211
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4298305238
All OpenAlex metadata
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https://openalex.org/W4298305238Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1806.08211Digital Object Identifier
- Title
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Reacting to Variations in Product Demand: An Application for Conversion\n Rate (CR) Prediction in Sponsored SearchWork title
- Type
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preprintOpenAlex work type
- Publication year
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2018Year of publication
- Publication date
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2018-05-25Full publication date if available
- Authors
-
Marcelo Tallis, Pranjul YadavList of authors in order
- Landing page
-
https://arxiv.org/abs/1806.08211Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1806.08211Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1806.08211Direct OA link when available
- Concepts
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Product (mathematics), Computer science, Outcome (game theory), The Internet, Machine learning, Search engine, Sampling (signal processing), Artificial intelligence, Data mining, Information retrieval, World Wide Web, Mathematics, Filter (signal processing), Mathematical economics, Geometry, Computer visionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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