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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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. ...

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 ...