--- a
+++ b/QueryExtraction/yake_test_query.py
@@ -0,0 +1,29 @@
+'''
+YAKE: https://github.com/LIAAD/yake
+
+YAKE! is a light-weight unsupervised automatic keyword extraction method which rests on text statistical features extracted from single documents to select the most important keywords of a text.
+We compare it against ten state-of-the-art unsupervised approaches (TF.IDF, KP-Miner, RAKE, TextRank, SingleRank, ExpandRank, TopicRank, TopicalPageRank, PositionRank and MultipartiteRank), and one supervised method (KEA).
+'''
+
+
+import yake
+
+
+language = "en"
+max_ngram_size = 3
+deduplication_thresold = 0.9
+deduplication_algo = 'seqm'
+windowSize = 1
+
+
+def yake_extract(text,topk=30):
+
+    custom_kw_extractor = yake.KeywordExtractor(lan=language, n=max_ngram_size, dedupLim=deduplication_thresold, dedupFunc=deduplication_algo, windowsSize=windowSize, top=topk, features=None)
+    keywords = custom_kw_extractor.extract_keywords(text)
+
+    results = []
+    for kw in keywords:
+        results.append(kw[0])
+
+    return results
+