1 Boolean Model

2 A document is represented as a set of keywords. Queries are Boolean expressions of keywords, connected by AND, OR, and NOT, including the use of brackets to indicate scope. –[[Rio & Brazil] | [Hilo & Hawaii]] & hotel & !Hilton] Output: Document is relevant or not. No partial matches or ranking.

3 Simple model based on set theory; Queries specified as Boolean expressions: –precise semantics; –neat formalism; –q = ka  (kb   kc). Terms are either present or absent. Thus, wij  {0,1}; Consider: –q = ka  (kb   kc) –vec(qdnf) = (1,1,1)  (1,1,0)  (1,0,0) –vec(qcc) = (1,1,0) is a conjunctive component. Boolean Model

4 q = ka  (kb   kc) sim(q,dj) = 1 if  vec(qcc) | (vec(qcc)  vec(qdnf))  (  ki, gi(vec(dj)) = gi(vec(qcc))) 0 otherwise (1,1,1) (1,0,0) (1,1,0) KaKb Kc Boolean Model

5 Popular retrieval model because: –Easy to understand for simple queries. –Clean formalism. Boolean models can be extended to include ranking. Reasonably efficient implementations possible for normal queries. Boolean Retrieval Model

6 Boolean Models  Problems Retrieval based on binary decision criteria with no notion of partial matching; No ranking of the documents is provided (absence of a grading scale); Very rigid: AND means all; OR means any. Information need has to be translated into a Boolean expression which most users find awkward; The Boolean queries formulated by the users are most often too simplistic; It is difficult to express complex user requests.

7 Boolean Models  Problems As a consequence, Boolean model frequently returns either too few or too many documents in response to a user query. Difficult to control the number of documents retrieved. –All matched documents will be returned. Difficult to rank output. –All matched documents logically satisfy the query. Difficult to perform relevance feedback. –If a document is identified by the user as relevant or irrelevant, how should the query be modified?