Rapper: a wrapper generator with linguistic knowledge (original) (raw)

Synthesizing structured text from logical database subsets

Proceedings of the 11th international conference on Extending database technology Advances in database technology - EDBT '08, 2008

In the classical database world, information access has been based on a paradigm that involves structured, schema-aware, queries and tabular answers. In the current environment, however, where information prevails in most activities of society, serving people, applications, and devices in dramatically increasing numbers, this paradigm has proved to be very limited. On the query side, much work has been done on moving towards keyword queries over structured data. In our previous work, we have touched the other side as well, and have proposed a paradigm that generates entire databases in response to keyword queries. In this paper, we continue in the same direction and propose synthesizing textual answers in response to queries of any kind over structured data. In particular, we study the transformation of a dynamically-generated logical database subset into a narrative through a customizable, extensible, and templatebased process. In doing so, we exploit the structured nature of database schemas and describe three generic translation modules for different formations in the schema, called unary, split, and join modules. We have implemented the proposed translation procedure into our own database front end and have performed several experiments evaluating the textual answers generated as several features and parameters of the system are varied. We have also conducted a set of experiments measuring the effectiveness of such answers on users. The overall results are very encouraging and indicate the promise that our approach has for several applications.

Semi-automatic wrapper generation for internet information sources

coopis, 1997

To simplify the task of obtaining information from the vast number of information sources that are available on the World Wide Web (WWW), we are building tools to build information mediators for extracting and integrating data from multiple Web sources. In a mediator based approach, wrappers are built around individual information sources, that provide translation between the mediator query language and the individual source. We present an approach for semi-automatically generating wrappers for structured internet sources. The key idea is to exploit formatting information in Web pages from the source to hypothesize the underlying structure of a page. From this structure the system generates a wrapper that facilitates querying of a source and possibly integrating it with other sources. We demonstrate the ease with which we are able to build wrappers for a number of Web sources using our implemented wrapper generation toolkit.

Creating relational data from unstructured and ungrammatical data sources

2008

Abstract In order for agents to act on behalf of users, they will have to retrieve and integrate vast amounts of textual data on the World Wide Web. However, much of the useful data on the Web is neither grammatical nor formally structured, making querying difficult. Examples of these types of data sources are online classifieds like Craigslist 1 and auction item listings like eBay.

Wrapper generation for semi-structured internet sources

ACM SIGMOD Record, 1997

With the current explosion of information on the World Wide Web (WWW) a wealth of information on many different subjects has become available on-line. Numerous sources contain information that can be classified as semistructured. At present, however, the only way to access the information is by browsing individual pages. We cannot query web documents in a database-like fashion based on their underlying structure. However, we can provide database-like querying for semi-structured WWW sources by building wrappers around these sources. We present an approach for semi-automatically generating such wrappers. The key idea is to exploit the formatting information in pages from the source to hypothesize the underlying structure of a page. From this structure the system generates a wrapper that facilitates querying of a source and possibly integrating it with other sources. We demonstrate the ease with which we are able to build wrappers for a number of internet sources in different domains using our implemented wrapper generation toolkit. ful to have the capability of issuing queries to this source which would allow us to query the source based on the structure in the pages.

Structured querying of Web text

2007

The Web contains a huge amount of text that is currently beyond the reach of structured access tools. This unstructured data often contains a substantial amount of implicit structure, much of which can be captured using information extraction (IE) algorithms. By combining an IE system with an appropriate data model and query language, we could enable structured access to all of the Web's unstructured data. We propose a general-purpose query system called the extraction database, or ExDB, which supports SQL-like structured queries over Web text. We also describe the technical challenges involved, motivated in part by our experiences with an early 90M-page prototype.

A Feasible Approach to Natural Language Database

1997

A truly natural language interface to databases also needs to be practical for actual implementation. We developed a new feasible approach to solve the problem and tested it successfully in a laboratory environment. The new result is based on metadata search, where the metadata grow in largely linear manner and the search is linguistics-free (allowing for grammatically incorrect and incomplete input). A new class of reference dictionary integrates four types of enterprise metadata: enterprise information models, database values, user-words, and query cases. The layered and scalable information models allow user-words to stay in original forms as users articulated them, as opposed to relying on permutations of individual words contained in the original query. A graphical representation method turns the dictionary into searchable graphs representing all possible interpretations of the input. A branch-and-bound algorithm then identifies optimal interpretations, which lead to SQL implementation of the original queries. Query cases enhance both the metadata and the search of metadata, as well as providing casebased reasoning to directly answer the queries. This design assures feasible solutions at the termination of the search, even when the search is incomplete (i.e., the results contain the correct answer to the original query). The necessary condition is that the text input contains at least one entry in the reference dictionary. The sufficient condition is that the text input contains a set of entries corresponding to a complete, correct single SQL query. Laboratory testing shows that the system obtained accurate results for most cases that satisfied only the necessary condition.

LODifier: generating linked data from unstructured text

2012

The automated extraction of information from text and its transformation into a formal description is an important goal in both Semantic Web research and computational linguistics. The extracted information can be used for a variety of tasks such as ontology generation, question answering and information retrieval.

Structured Querying of Web Text Data: A Technical Challenge

Conference on Innovative Data Systems Research, 2007

A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing

International Journal of Mathematical Sciences and Computing, 2015

A natural language query builder interface retrieves the required data in structured form from database when query is entered in natural language. The user need not necessarily have sufficient technical knowledge of structured query language statements so nontechnical users can also use this proposed model. In natural language parsing, getting highly accurate syntactic analysis is a crucial step. Parsing of natural languages is the process of mapping an input string or a natural language sentence to its syntactic representation. Constituency parsing approach takes more time for parsing. So, natural language query builder interface is developed in which the parsing of natural language sentence is done by using dependency parsing approach. Dependency parsing technique is widespread in natural language domain because of its state-of-art accuracy and efficiency and also it performs best. In this paper, the buffering scheme is also proposed for natural language statements which will not load the whole sentence if it was done previously. Also there was a need of generalized access to all tables from database which is handled in this system.

Hierarchical wrapper induction for semistructured information sources

Autonomous Agents and Multi-Agent …, 2001

With the tremendous amount of information that becomes available on the Web on a daily basis, the ability to quickly develop information agents has become a crucial problem. A vital component o f a n y W eb-based information agent is a set of wrappers that can extract the relevant data from semistructured information sources. Our novel approach to wrapper induction is based on the idea of hierarchical information extraction, which turns the hard problem of extracting data from an arbitrarily complex document i n to a series of simpler extraction tasks. We introduce an inductive algorithm, stalker, that generates high accuracy extraction rules based on user-labeled training examples. Labeling the training data represents the major bottleneck in using wrapper induction techniques, and our experimental results show that stalker requires up to two orders of magnitude fewer examples than other algorithms. Furthermore, stalker can wrap information sources that could not be wrapped by existing inductive techniques.

Rapper: a wrapper generator with linguistic knowledge (original) (raw)

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