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@@ -3,47 +3,54 @@ language:
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  - en
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  pipeline_tag: text-classification
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  widget:
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- - title: Rating Example
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- text: '4.7'
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- - title: Reviews Example
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- text: '(188)'
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- - title: Reviews Example 2
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- text: '188'
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- - title: Reviews Example 3
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- text: 'No Reviews'
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- - title: Price Example
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- text: '$'
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- - title: Type Example
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- text: 'Coffee shop'
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- - title: Address Example
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- text: 'Frederick, MD'
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- - title: Address Example 2
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- text: '552 W 48th St'
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- - title: Address Example 3
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- text: 'In Hilton Hotel'
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- - title: Hours Example
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- text: 'Closed'
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- - title: Hours Example 2
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- text: 'Opens 7 AM Fri'
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- - title: Hours Example 3
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- text: 'Permanently closed'
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- - title: Service Option Example
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- text: 'Dine-in'
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- - title: Service Option Example 2
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- text: 'Takeout'
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- - title: Service Option Example 3
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- text: 'Delivery'
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- - title: Phone Example
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- text: '(301) 000-0000'
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- - title: Years In Business Example
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- text: '5+ Years in Business'
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- - title: Button Text Example
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- text: 'Directions'
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- - title: Description Example
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- text: 'Provides: Auto maintenance'
 
 
 
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  ---
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- <h1 align="center">BERT-based Classification Model for Google Local Listing</h1>
 
 
 
 
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  <p align="center">
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  This repository contains a BERT-based classification model developed using the Hugging Face library, and a dataset gathered by <a href='https://serpapi.com/google-local-api'>SerpApi's Google Local API</a>. The model is designed to classify different texts extracted from Google Local Listings.
@@ -154,8 +161,10 @@ Please refer to the documentation of SerpApi's Google Local API and Google Local
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  <strong>References:</strong>
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- <li>SerpApi's Google Local API: <a href ="https://serpapi.com/google-local-api">https://serpapi.com/google-local-api</a></li>
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- <li>SerpApi's Google Local Pack API: <a href="https://serpapi.com/local-pack">https://serpapi.com/local-pack</a></li>
 
 
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  </div>
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@@ -183,8 +192,8 @@ Please refer to the documentation of SerpApi's Google Local API and Google Local
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  </li>
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  <li>The model may be susceptible to error in one word entries. This is a minority of the cases, and it could be fixed with assurance scores.For Example:
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  <ul style="list-style-type: circle">
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- <li><code>"Sushi"</code> &rarr; <code>address(0.984), type(0.0493)</code></li>
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- <li><code>"Diagorou 4"</code> &rarr; <code>address(0.999)</code></li>
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  </ul>
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  </li>
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  <li>The model cannot differentiate between extra parts that are extracted in SerpApi's Google Local API and Google Local Pack API. These parts are not feasible to extract via Classification Models.</li>
@@ -210,4 +219,4 @@ While we understand the value of transparency, we also recognize the need to str
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  </p>
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  <p align="center">
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  We appreciate your understanding and support in our commitment to responsible and ethical data practices. If you have any further questions or concerns, please feel free to reach out to us.
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- </p>
 
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  - en
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  pipeline_tag: text-classification
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  widget:
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+ - title: Rating Example
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+ text: '4.7'
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+ - title: Reviews Example
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+ text: (188)
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+ - title: Reviews Example 2
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+ text: '188'
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+ - title: Reviews Example 3
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+ text: No Reviews
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+ - title: Price Example
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+ text: $
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+ - title: Type Example
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+ text: Coffee shop
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+ - title: Address Example
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+ text: Frederick, MD
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+ - title: Address Example 2
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+ text: 552 W 48th St
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+ - title: Address Example 3
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+ text: In Hilton Hotel
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+ - title: Hours Example
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+ text: Closed
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+ - title: Hours Example 2
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+ text: Opens 7 AM Fri
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+ - title: Hours Example 3
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+ text: Permanently closed
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+ - title: Service Option Example
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+ text: Dine-in
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+ - title: Service Option Example 2
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+ text: Takeout
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+ - title: Service Option Example 3
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+ text: Delivery
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+ - title: Phone Example
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+ text: (301) 000-0000
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+ - title: Years In Business Example
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+ text: 5+ Years in Business
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+ - title: Button Text Example
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+ text: Directions
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+ - title: Description Example
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+ text: 'Provides: Auto maintenance'
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+ license: mit
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+ datasets:
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+ - serpapi/local-results-en
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  ---
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+ <h1 align="center">BERT-based Classification Model for Google Local Listings</h1>
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+
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+ <p align="center">
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+ <img src="https://camo.githubusercontent.com/6c920f0b551360ca3257308e0f3547fe538496b9cb332d6a208992030abf6c3d/68747470733a2f2f736572706170692e636f6d2f616e64726f69642d6368726f6d652d353132783531322e706e67" alt="The Logo of SerpApi" width="200" height="200">
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+ </p>
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  <p align="center">
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  This repository contains a BERT-based classification model developed using the Hugging Face library, and a dataset gathered by <a href='https://serpapi.com/google-local-api'>SerpApi's Google Local API</a>. The model is designed to classify different texts extracted from Google Local Listings.
 
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  <strong>References:</strong>
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+ <ul style="text-align: center; list-style-position: inside;">
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+ <li>SerpApi's Google Local API: <a href ="https://serpapi.com/google-local-api">https://serpapi.com/google-local-api</a></li>
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+ <li>SerpApi's Google Local Pack API: <a href="https://serpapi.com/local-pack">https://serpapi.com/local-pack</a></li>
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+ </ul>
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  </div>
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  </li>
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  <li>The model may be susceptible to error in one word entries. This is a minority of the cases, and it could be fixed with assurance scores.For Example:
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  <ul style="list-style-type: circle">
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+ <li><code>"Sushi"</code> &rarr; <code>address(0.984), type(0.0493) [Correct Label is type]</code></li>
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+ <li><code>"Diagorou 4"</code> &rarr; <code>address(0.999) [Correct address in same listing]</code></li>
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  </ul>
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  </li>
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  <li>The model cannot differentiate between extra parts that are extracted in SerpApi's Google Local API and Google Local Pack API. These parts are not feasible to extract via Classification Models.</li>
 
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  </p>
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  <p align="center">
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  We appreciate your understanding and support in our commitment to responsible and ethical data practices. If you have any further questions or concerns, please feel free to reach out to us.
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+ </p>