What are the major problems with relevance feedback in information retrieval

List down the drawbacks of relevance feedback query expansion, Why relevance feedback is not widely applied?, basic problems with relevance feedback, When to use relevance feedback?

Question: Why is relevance feedback not widely used? / What are the major problems with relevance feedback?   Answer: Users were sometimes reluctant to provide explicit feedback. They may not be interested in interacting with the search engine. Rather, they may go for trying different query. The user’s knowledge is insufficient to formulate the initial query. User should have sufficient knowledge to represent their information needs through initial query. The cases like misspellings and vocabulary mismatch cannot be handled by relevance feedback alone. Relevance feedback is expensive. It results in long queries that require more computation to retrieve. Search engines process lots of queries and allow little time for each one. Makes it harder to understand why a particular document was retrieved after applying relevance feedback.

Related links/questions

• How to improve the recall of an information retrieval system

• What are the global resources for query expansion / reformulation?

• Machine learning multiple choices questions with detailed answers - home page

• List down the local methods for improving recall of IR systems

• What are the components of a benchmark data collection?

• What are the drawbacks of Boolean retrieval model?

• Common preprocessing steps and their significance in information retrieval

             

Keywords

When to use relevance feedback query expansion technique?

When not to use relevance feedback?

List the basis problems with relevance feedback

Query expansion using relevance feedback

How to improve search results using relevance feedback

 

What are the possible problems with Boolean retrieval models

List down the problems with Boolean retrieval model, What are the notable drawbacks of Boolean retrieval model, Boolean model is one of the information retrieval model, why the result from Boolean model is not ranked

Question: What are the possible problems with Boolean retrieval models?   Answer: Very rigid: AND means all; OR means any. Queries are Boolean expressions of keywords connected by AND, OR, and NOT, including the use of brackets. Difficult to express complex user requests. We cannot express complex queries as only keywords are processed for retrieval purpose. 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.  A document is identified by the user as relevant or irrelevant. No further data are collected. It makes it hard to perform relevance feedback.

Related links/questions

• How to improve the recall of an information retrieval system

• What are the global resources for query expansion / reformulation?

• Machine learning multiple choices questions with detailed answers - home page

• List down the local methods for improving recall of IR systems

• What are the drawbacks of relevance feedback in improving search results

• What are the components of a benchmark data collection?

• What are the drawbacks of Boolean retrieval model?

• Common preprocessing steps and their significance in information retrieval

             

Keywords

Drawbacks of boolean retrieval model

Why the result of a boolean model is not ranked?

Why is it hard to represent complex queries in boolean model?

Can we use relevance feedback in boolean information retrieval model?