Web Mining and Search course practice project

Establish vector space model in practice to retrieve relevence top 10 document with user query.

pip install -r requirements.txt

python main.py --query {query_str}

Notice :

• query_str should be input within " " .

• queries should be seperated by space .

Example :

python main.py --query "Trump Biden Taiwan China"

Output : top 10 news ID with scores

• Term Frequency Weighting + Cosine Similarity

• Term Frequency Weighting + Euclidean Distance

• TF-IDF Weighting + Cosine Similarity

• TF-IDF Weighting + Euclidean Distance

• Relevence Feedback - TF-IDF + Cosine Similarity

The code runs for a long time on my computer. It costs more than 30 minutes :(