The IQS is an iterative approach for optimizing short keyword queries given a prototype document through interaction with an opaque search engine such as Twitter.
Project description
Iterative Query Selection (IQS)
Python Package Overview
- Performs the IQS algorithm on various queries by providing a simple API for accessing all its functionality.
- Modify the quality of the search results from Twitter by setting different parameters.
- Designed for users with technical background.
- Download the package using pip install IQS-algorithm
Check out the IQS algorithm web platform in the following link: IQS Web
The platform can help you explore the IQS algorithm benefits:
- Search and retrieve data from Twitter's website using the IQS algorithm.
- Displays results from the experiment described in the academic paper. In the experiment, the IQS algorithm is compared to another algorithm in the field (ALMIK) on a specific dataset.
- Presenting the academic paper with Q&A
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file IQS_algorithm-1.0.0-py3-none-any.whl.
File metadata
- Download URL: IQS_algorithm-1.0.0-py3-none-any.whl
- Upload date:
- Size: 69.4 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.9.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e57915f1026d30ba3a5454cddcba970134458128557a3c367f449d46bac16217
|
|
| MD5 |
384ff41ac7a9dfe8edc298e247384ef3
|
|
| BLAKE2b-256 |
70e603898be1c4cb62792417dfc13800da17af8f114cfbecbb351e305211a2af
|