Search method

lucene method

• data set

• jiangkaipeng:

• different method result

different result in lucene

method	Default	BM25	LMDirichlet	DFR	LMJelinekMercer	IB
Accary	0.66228	0.66228	0.4091	0.65476	0.65476	0.6666

boost keyword

• boost the query keyword using IDF

boost keyword in lucene

method	Default	idf_train	idf_train_norm	idf_baidu	idf_baidu_norm
Accary	0.66228	0.651629	0.57644	0.647869	0.65288

• TFIDF Formula

• coord(q,d)*query_boost*query_norm*sum(idf^2 * tf * term_boost * norm(t,d)) [1]

• add the new keyword value from proMe method

our method

different result in lucene

method	lucene	vsm_idf(haiguan)	VSM_idf(baidu)	vsm_idf(tain)	vsm_idf(calculate)
Accary	0.6628	0.6228	0.6197	0.5827	0.5426

synonyms method

• fuzzy match

• calculate the similarity value = 1/(5-5*av_value).where av_value = average(word2vec+Synonyms forest+hownet).

• lucene

• lucene4.6 already added synonyms method (org.apache.lucene.analysis.synonym[2]) like :(a -> x) (a b -> y) (b c d -> z) or extend the query.

find

• 采用最细粒度分词(对于标准问题在建立索引时，模板不用),可以提高正确率。61=>66.对于标准问题建索引时.
• 对输入的问题不应用细粒度分词（细粒度的59%，不用66%）。
• lucene4.6 已经增加了同义词拓展[3]