Semantic search

• SEMANTIC SEARCH

• PRESENTED BY:
• Group No:13
• Jai Mashalkar 113050007
• Khushraj Madnani 113050041
• Lahari Poddar 113050029

• SEMANTIC SEARCH

• Semantic search seeks to improve search accuracy by understanding searcher’s intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results.

• MOTIVATION FOR SEMANTIC SEARCH

• SEMANTIC SEARCH TECHNOLOGY

• Semantically Relatable Sets
• Query Expansion
• Relevance Feedback

• SEMANTICALLY RELATABLE SETS

• SEMANTICALLY RELATABLE SET

• A semantically relatable set (SRS) of a sentence is a group of unordered words in the sentence (not necessarily consecutive) that appear in the semantic graph of the sentence as linked nodes.

• FORMS OF SRS

• {CW,CW}
• {CW,FW,CW}
• {FW,CW}
• CW: Content Word or Clause
• FW: Function Words
• Example: The girl borrowed a book on AI from library.
• CW: girl, borrowed, book, AI, library
• FW: the, a, on, from

• THE GIRL BORROWED A BOOK ON AI FROM LIBRARY

• borrowed

• library

• book

• girl

• AI

• agent

• object

• place

• the: definite

• a: indefinite

• from: modifier

• on: modifier

• modifier

• past tense

• THE GIRL BORROWED A BOOK ON AI FROM LIBRARY

• Sets Formed:
• {the,girl}
• {girl,borrowed}
• {borrowed,book}
• {book,on,AI}
• {borrowed,from,library}
• {a,book}

• THE PROFESSOR ANNOUNCED THAT HE WILL CONDUCT AN EXTRA LECTURE ON SUNDAY

• announced

• SCOPE

• professor

• agent

• the: definite

• object

• that: modifier

• THE PROFESSOR ANNOUNCED THAT HE WILL CONDUCT AN EXTRA LECTURE ON SUNDAY

• SCOPE:

• conduct

• sunday

• lecture

• he

• extra

• agent

• object

• time

• on: modifier

• modifier

• Will: Future Tense

• an: indefinite

• SETS FORMED

• {the,professor}
• {professor,announced}
• {announced.that,SCOPE}
• SCOPE:{he,conduct}
• SCOPE:{will,conduct}
• SCOPE:{conduct,lecture}
• SCOPE:{conduct,on,sunday}
• SCOPE:{extra,lecture}
• SCOPE:{an,lecture}

• SRS BASED SEARCH

• Rq(d) = Relevance of the document d to the query q
• |Sd| = Number of sentences in the document d
• rq(s) = Relevance of sentence s to the query q

• The relevance score for a document d:

• The relevance of the sentence s to the query q :

• weight(srs) = weight of the SRS srs.
• press(srs) = true if srs is present in sentence s, false otherwise.

• ANALYSIS OF SRS

• SRS based search technique gives very high precision value ( the fraction of retrieved instances that are relevant) compared to tf-idf based search.
• But falls short of tf-idf based search due to its low recall( the fraction of relevant instances that are retrieved).

• LOW RECALL

• REASONS:
• Morphological Divergence
• Eg: Apparel for man: Clothes for men
• Synonymy/Hypernymy/Hyponymy Divergence
• Eg: Color: red/blue
• Physical Separation Divergence
• Eg: Book on AI: AI book