Articulating Information Needs in

Transcription

1 Articulating Information Needs in XML Query Languages Jaap Kamps, Maarten Marx, Maarten de Rijke and Borkur Sigurbjornsson Gonçalo Antunes

2 Motivation Users have increased access to documents with additional semantic information through XML markup. A new approach for querying documentcentric XML is needed. Understand which approach to query XML documents can be more effective in satisfying the information needs of users.

3 Problem How do users exploit the additional expressive power of structural constraints in their queries, what queries do users formulate, and what is the meaning of these queries? What is the effect on retrieval performance of adding structural constraints to queries? What is the appropriate query language for XML retrieval?

4 Results Structural constraints are mainly used as search hints, not as strict requirements: hierarchical structure of documents used in one third of the queries Three quarters of the queries put constraints on the context of the element to retrieve Adding structural constraints has a positive effect on early precision and a negative effect on overall recall A typology of the different uses of content and structure queries, and intuitive mathematical models of users knowledge of a set of XML documents, and the formulation of query languages which exactly fit this knowledge are provided

5 INEX -Initiative For The Evaluation Of XML Retrieval Initiative to evaluate the retrieval methods of participants Uniform scoring procedures and comparison of results Large testbed of XML documents (circa xml documents) Queries: CO queries: the retrieval system identifies the most appropriate XML elements to return to the system CAS queries: structural constraints explicitly stated and can refer the types of elements to retrieve

6 CAS topic (2003)

7 CO topic (2003)

8 NEXI Query Language (2004) Based on Xpath Uses only the descendent axis, from the current node (e.g. // ) Uses only the booleans ande or in filter expressions Should contain at least one about function free text search The rightmost filter should be an about function

9 NEXI Query Language Examples //sec[about(., vector space model )] //article[about(., web search engine )]//sec[about (., vector space model )]

10 How do users exploit the additional expressive power of structural constraints in their queries?

11 Requested Elements Queries allow the users to specify the types of elements that should be return as answers.

12 Elements Judged Relevant Relevance assessments are made focusing on highly specific and highly exaustive elements.

13 Requested versus Relevant Elements Investigate how often the element that is judged relevant actually has the tag name specified in the query. Frequency of relevant elements on columns Elements with tag names on rows

14 So, how do users exploit the additional expressive power of structural constraints in their queries? Assessors felt that their information needs where also satisfied by elements not respecting the target constraints In most cases, elements satisfying the target constraints are the largest category Element names as requested in the query can only be considered a retrieval hint, and not a strict constraint on the output.

15 What is the effect on retrieval performance of adding structural constraints to queries?

16 Queries Structured query: e.g., //article[about(.//abs, sorting)]//sec[about(., heap sort)] Target-only query: e.g., //article//sec[about(., sorting heap sort)] Content-only query: e.g., //*[about(., sorting heap sort)]

17 Experimental Setup Evaluation performed using trec_evaland EvalJ Three runs using the queries Runs differ in the amount of structure, ranging from no structured constraints used to all structured constraints used.

18 Processing Decomposition: The query is decomposed into a sequence of pairs of the form (location path, content description), one for each about function. (//article//abs, sorting ) (//article//sec, heap sort ) Retrieval: For each pair, XML elements satisfying the location path are scored using a language model retrieval approach. Mixture: For each element satisfying the target constraints, it is considered other elements satisfying the tree pattern of the query (consider the corresponding abstract elements for a particular section element). Result: the sum of scores of the aboutfunctions for elements satisfying the target constraints.

19 Retrieval Model (for the Retrieval Step) Probability of generating ti given element e Probability of generating ti given the collection Interpolation factor (smoothing) B=1,5 if target element B= 0 if other element Sum of the tf s of all the terms of the element e

20 Results Bigger precision on contentonly queries Bigger precision on the first five results

21 So, what is the effect on retrieval performance of adding structural constraints to queries? Structured queries do not lead to improved mean average precision scores, at higher recall levels. Structured queries lead to significantly superior early precision scores; Structural constraints function as a precision enhancing device. In general, content-only queries outperform structured queries.

22 What are the typical sorts of content- and-structure queries that users formulate in the NEXI query language?

23 Dimensions Hierarchy: whether the query uses hierarchical information about the documents. Context: whether the query puts content constraints on text occurring outside the element to be returned.

24 Categories //sec[about(., xxx )] //sec[about(., yyy ) and about(//abs, xxx )] //sec[about(., xxx ) and about(.//thm, yyy )] //sec[about(., xxx ) and about(.//thm, yyy ) and about(//abs, zzz )]

25 How structure is used?

26 So, what are the typical sorts of content-and-structure queries that users formulate in the NEXI query language? The hierarchical nature of the documents is used in one third of the examined queries. Almost three quarters of the queries use content constraints on particular elements occurring in the context of elements to be returned.

27 Is the NEXI language the most appropriate one for XML retrieval?

28 NEXI query language Is a restricted form of Xpath Two competing forces: safety, which reduces expressive power, and completeness, which asks for as much expressivity as possible. User profiles: Structure-Unaware users and Hierarchy-Aware users

29 Structure-Unaware Users The typical queries are restricted search and contextual content information (they only know tag names) Structure-unaware queries (Bisimulation property): //tag[p], where P is a predicate created using and, or, and not from location paths self::tag and queries of the form //tag[p] it simply says that somewhere on the document there is a tag element making P true. e.g.: //section[//abstract]

30 Hierarchy-Aware Users Have some clue about the hierarchical structure of the documents E.g. know that paragraphs are below sections, but need not know of elements in between. Vertical simulation property. //tag[p], P=.//tag[Q] ; //section[.//paragraph]]

31 Results Structural constraints are mainly used as search hints, not as strict requirements: hierarchical structure of documents used in one third of the queries Three quarters of the queries put constraints on the context of the element to retrieve Adding structural constraints has a positive effect on early precision and a negative effect on overall recall A typology of the different uses of content and structure queries, and intuitive mathematical models of users knowledge of a set of XML documents, and the formulation of query languages which exactly fit this knowledge are provided