Query Languages

1. Query Languages J. H. Wang Mar. 25, 2008

2. Text User Interface 4, 10 user need Text Text Operations 6, 7 logical view logical view Query Operations DB Manager Module Indexing user feedback 5 8 inverted file query Searching Index 8 retrieved docs Text Database Ranking ranked docs 2 The Retrieval Process

3. Outline • Keyword-Based Querying • Pattern Matching • Structural Queries • Query Protocols • Trends and Research Issues

4. Data Retrieval Information Retrieval Keyword-Based Querying • A query is the formulation of a user information need • Keyword-based queries are popular 1. Single-Word Queries 2. Context Queries 3. Boolean Queries 4. Natural Language

5. Single-Word Queries • A query is formulated by a word • A document is formulated by long sequences of words • A word is a sequence of letters surrounded by separators • What are letters and separators? • e.g, ’on-line’ • The division of the text into words is not arbitrary

6. Context Queries • Definition - Search words in a given context • Types • Phrase • a sequence of single-word queries • e.g, ‘… enhance the retrieval …’ • Proximity • a sequence of single words or phrases, and a maximum allowed distance between them are specified • e.g, within distance (enhance, retrieval, 4) will match ‘…enhance the power of retrieval…’

7. Boolean Queries • Definition • A syntax composed of atoms that retrieve documents, and of Boolean operators which work on their operands • e.g, translation AND syntax OR syntactic • Fuzzy Boolean • Retrieve documents appearing in some operands (The AND may require it to appear in more operands than the OR)

8. Natural Language • Generalization of “fuzzy Boolean” • A query is an enumeration of words and context queries • All the documents matching a portion of the user query are retrieved

9. Pattern Matching • Data retrieval • A pattern is a set of syntactic features that must occur in a text segment • Types • Words • Prefixes • e.g ‘comput’->’computer’ , ’computation’, ’computing’, etc • Suffixes • e.g ‘ters’->’computers’, ’testers’, ’painters’, etc • Substrings • e.g ‘tal’->’coastal’, ’talk’, ’metallic’, etc • Ranges • between ‘held’ and ‘hold’ -> ’hoax’ and ‘hissing’

10. Allowing Errors • Retrieve all text words which are ‘similar’ to the given word • edit distance: the minimum number of character insertions, deletions, and replacements needed to make two strings equal, e.q , ‘flower’ and ‘flo wer’ • maximum allowed edit distance: the query specifies the maximum number of allowed errors for a word to match the pattern

11. Regular expressions • union:if e1 and e2 are regular expressions , then(e1|e2) matches what e1 or e2 matches • concatenation:if e1 and e2 are regular expressions, the occurrences of (e1e2) are formed by the occurrences of e1 immediately followed by those of e2 • repetition:if e is a regular expression , then (e*) matches a sequence of zero or more contiguous occurrence of e • ‘pro(blem|tein)(s|є)(0|1|2)*’ -> ’problem02’ and ‘proteins’

12. Structural Queries • Mixing contents and structure in queries - contents: words, phrases, or patterns - structural constraints: containment, proximity, or other restrictions on structural elements • Three main structures - Fixed structure - Hypertext structure - Hierarchical structure

13. Fixed Structure Document: a fixed set of fields Ex: a mail has a sender, a receiver, a date, a subject and a body field Search for the mails sent to a given person with “football” in the Subject field

14. Hypertext A hypertext is a directed graph where nodes hold some text (text contents) the links represent connections between nodes or between positions inside nodes (structural connectivity)

15. Hypertext : WebGlimpse WebGlimpse: combine browsing and searching on the Web

16. Hierarchical Structure

17. Hierarchical Structure

18. Hierarchical Structure • PAT Expressions • Overlapped Lists • Lists of References • Proximal Nodes • Tree Matching

19. Query Protocols • Used automatically by software applications to query text database • Not intended for human use • “Protocols” rather than “languages” • Z39.50 • WAIS (Wide Area Information Service)

20. Z39.50 • American National Standard Information Retrieval Application Service Definition • Can be implemented on any platform • Query bibliographical information using a standard interface between the client and the host database manager • Z39.50 protocol is part of WAIS

21. Z39.50 Brief History • Z39.50-1988(version 1) • Z39.50-1992(version 2) • Z39.50-1995(version 3) • Version 4, development began in Autumn 1995

22. Using Z39.50 over the WWW WWW Client WWW Z39.50 Z39.50 Server Repository Digital library Z39.50 Client

23. WAIS (Wide Area Information Service) • Beginning in the 1990s • Query databases through the Internet

24. Model Queries allowed word, set operations words words words Boolean Vector Probabilistic BBN Trends and Research Issues Relationship between types of queries and models

25. Query Language Taxonomy The types of queries covered and how they are structured

26. PAT Tree Expression • The model allows for the areas of a region to overlap or nest

27. Overlapped Lists • The model allows for the areas of a region to overlap, but not to nest • It is not clear, whether overlapping is good or not for capturing the structural properties

28. Lists of References • Overlap and nest are not allowed • All elements must be of the same type, e.g only sections, or only paragraphs. • A reference is a pointer to a region of the database.

29. Proximal Nodes • This model tries to find a good compromise between expressiveness and efficiency. • It does not define a specific language, but a model in which it is shown that a number of useful operators can be included achieving good efficiency.

30. Tree Matching • The leaves of the query can be not only structural elements but also text patterns, meaning that the ancestor of the leaf must contain that pattern.