Skip to content

Use MMR as the output score and sorting key #227

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
hberinsky wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Use MMR as the output score and sorting key #227

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions keybert/_mmr.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,7 @@ def mmr(
# Initialize candidates and already choose best keyword/keyphras
keywords_idx = [np.argmax(word_doc_similarity)]
candidates_idx = [i for i in range(len(words)) if i != keywords_idx[0]]
words_mmr = [(1 - diversity) * np.max(word_doc_similarity)]

for _ in range(min(top_n - 1, len(words) - 1)):
# Extract similarities within candidates and
Expand All @@ -55,15 +56,14 @@ def mmr(
1 - diversity
) * candidate_similarities - diversity * target_similarities.reshape(-1, 1)
mmr_idx = candidates_idx[np.argmax(mmr)]
words_mmr.append(np.max(mmr))

# Update keywords & candidates
keywords_idx.append(mmr_idx)
candidates_idx.remove(mmr_idx)

# Extract and sort keywords in descending similarity
keywords = [
(words[idx], round(float(word_doc_similarity.reshape(1, -1)[0][idx]), 4))
for idx in keywords_idx
]
keywords = [(words[keywords_idx[i]], round(float(words_mmr[i]), 4))
for i in range(len(keywords_idx))]
keywords = sorted(keywords, key=itemgetter(1), reverse=True)
return keywords