2009 Proceeding- General Chair:
- M. Tamer Özsu,
- Program Chairs:
- Yi Chen,
- Lei Chen
Information search is an indispensable component of our lives. Web search engines are widely used for searching textual documents, images, and video. However, there are also vast collections of structured and semi-structured data both on the Web and in enterprises, such as relational databases, XML data, etc. Traditionally, to access these resources, a user must learn structured or semi-structured query languages, and must be able to access data schemas, which are most likely heterogeneous, complex, and fastevolving. To relieve web and scientific users from the learning curve and enable them to easily access structured and semi-structured data, there is a growing research interest to support keyword search on these data sources.
The first International Workshop on Keyword Search on Structured Data (KEYS 2009) is held in Providence, Rhode Island, USA on 28th June, 2009, in conjunction with SIGMOD 2009 conference, and aims to encourage researchers from both academia and industry communities to discuss the opportunities and challenges in keyword search on (semi-)structured data, and to present the key issues and novel techniques in this area. In response to the call for papers, KEYS 2009 has attracted 25 submissions. The submissions are highly diversified, coming from Canada, China, Germany, Italy, Japan, Greece, Singapore, Sweden, Thailand, and USA, resulting in an international final program. All submissions were peer reviewed by three program committee members. The program committee selected 6 full research papers and 4 demo and poster papers for inclusion in the proceeding. The accepted papers covered a wide range of research topics and novel applications on keyword search on structured data.
Proceeding Downloads
Structured data and web documents: better together?
Keyword search over structured databases is silo-ed from web search in that their results are independent of those from web search. We claim that keyword search can benefit significantly from the knowledge of web documents and results of web search. ...
Querying text databases and the web: beyond traditional keyword search
Traditional keyword search---where a query is a list of keywords and query results are a relevance-ordered list of documents---is, of course, a powerful query paradigm for text databases and the Web. However, more expressive query paradigms, where both ...
Hierarchical result views for keyword queries over relational databases
Enabling keyword queries over relational databases (KQDB) benefits a large population of users who have difficulty in understanding the database schema or using SQLs. However, since there are different interpretations for a query, the results of KQDB ...
Efficient top-k algorithms for fuzzy search in string collections
An approximate search query on a collection of strings finds those strings in the collection that are similar to a given query string, where similarity is defined using a given similarity function such as Jaccard, cosine, and edit distance. Answering ...
A first study on strategies for generating workflow snippets
Workflows are increasingly being used to specify computational tasks, from simulations and data analysis to the creation of Web mashups. Recently, a number of public workflow repositories have become available, for example, myExperiment for scientific ...
Query segmentation using conditional random fields
A growing mount of available text data are being stored in relational databases, giving rise to an increasing need for the RDBMSs to support effective text retrieval. In this paper, we address the problem of keyword query segmentation, i.e., how to ...
Keyword query cleaning using hidden Markov models
In this paper, we consider the problem of keyword query cleaning for structured databases from a probabilistic approach. Keyword query cleaning consists of rewriting the user query, segmenting the keywords, matching each segment to database items, and ...
Do we mean the same?: disambiguation of extracted keyword queries for database search
Users often try to accumulate information on a topic of interest from multiple information sources. In this case a user's informational need might be expressed in terms of an available relevant document, e.g. a web-page or an e-mail attachment, rather ...
Building search applications with Marklogic Server
Keyword search is recognized as an important technique to unlocking the information found in both structured and semi-structured information. With XML as the data model and XQuery as the programming language, MarkLogic Server[1] allows developers to ...
XML keyword query refinement
Existing works in XML keyword search have addressed the problem of finding matching results of a query. However, user input queries always contain irrelevant or mismatched terms, spelling errors etc, which causes the search results to be either empty or ...
Language-model-based ranking in entity-relation graphs
We propose a language-model-based ranking approach for SPARQL-like queries on entity-relationship graphs. Our ranking model supports exact matching, approximate structure matching, and approximate matching with text predicates. We show the effectiveness ...
Generic and effective semi-structured keyword search
Current semi-structured keyword search and natural language query processing systems use ad hoc approaches to take advantage of structural information. Although intuitive, they are ultimately ad hoc. We have developed the concept of coherency ranking ...
DBDOC: querying and browsing databases and interrelated documents
Large collections of documents are commonly created around a database, where a typical database schema may contain hundreds of tables and thousands of columns. We developed a system based on SQL code generation and User-Defined Functions that analyzes ...
- Proceedings of the First International Workshop on Keyword Search on Structured Data