Rodolfo A. Pazos Rangel

A domain independent natural language interface to databases capable of processing complex queries

We present a method for creating natural language interfaces to databases (NLIDB) that allow for translating natural language queries into SQL. The method is domain independent, i.e., it avoids the tedious process of configuring the NLIDB for a given domain. We automatically generate the domain dictionary for query translation using semantic metadata of the database. Our semantic representation of a query is a graph including information from database metadata. The query is translated taking into account the parts of speech of its words (obtained with some linguistic processing). Specifically, unlike most existing NLIDBs, we take seriously auxiliary words (prepositions and conjunctions) as set theory operators, which allows for processing more complex queries. Experimental results (conducted on two Spanish databases from different domains) show that treatment of auxiliary words improves correctness of translation by 12.1%. With the developed NLIDB 82of queries were correctly translated (and thus answered). Reconfiguring the NLIDB from one domain to the other took only ten minutes.

Spanish Natural Language Interface for a Relational Database Querying System

The fast growth of Internet is creating a society where the demand on information storage, organization, access, and analysis services is continuously growing. This constantly increases the number of inexperienced users that need to access databases in a simple way. Together with the emergence of voice interfaces, such a situation foretells a promising future for database querying systems using natural language interfaces. We describe the architecture of a relational database querying system using a natural language (Spanish) interface, giving a brief explanation of the implementation of each of the constituent modules: lexical parser, syntax checker, and semantic analyzer.

Issues in translating from natural language to SQL in a domain-independent natural language interface to databases

This paper deals with a domain-independent natural language interface to databases (NLIDB) for the Spanish language. This NLIDB had been previously tested for the Northwind and Pubs domains and had attained good performance (86% success rate). However, domain independence complicates the task of achieving high translation success, and to this end the ATIS (Air Travel Information System) database, which has been used by several natural language interfaces, was selected to conduct a new evaluation. The purpose of this evaluation was to asses the efficiency of the interface after the reconfiguration for another domain and to detect the problems that affect translation success. For the tests a corpus of queries was gathered and the results obtained showed that the interface can easily be reconfigured and that attained a 50% success rate. When the found problems concerning query translation were analyzed, wording deficiencies of some user queries and several errors in the synonym dictionary were discovered. After correcting these problems a second test was conducted, in which the interface attained a 61.4% success rate. These experiments showed that user training is necessary as well as a dialogue system that permits to clarify a query when it is deficiently formulated.

Cellular Processing Algorithms

In this chapter we propose a new class of cellular algorithms. There exists a variety of cellular algorithm approaches but most of them do not structure the search process. In this work we propose a cellular processing approach to solve optimization problems. The main components of these algorithms are: the processing cells (PCells), the communication between PCells, and the global and local stagnation detection. The great flexibility and simplicity of this approach permits pseudo-parallelization of one or several different metaheuristics. To validate our approach, the linear ordering problem with cumulative costs (LOPCC) was used to describe two cellular processing algorithms, whose performance was tested with standard instances. The experimental results show that the cellular processing algorithms increase solution quality up to 3.6% and reduce time consumption up to 20% versus the monolithic approach. Also the performance of these algorithms is statistically similar to those of the state-of-the-art solutions, and they were able to find 38 new best-known solutions (i.e., not previously found by other algorithms) for the instances used. Finally, it is important to point out that these encouraging results indicate that the field of cellular processing algorithms is a new and rich research area.

Features and Pitfalls that Users Should Seek in Natural Language Interfaces to Databases

Natural Language Interfaces to Databases (NLIDBs) are tools that can be useful in making decisions, allowing different types of users to get information they need using natural language communication. Despite their important features and that for more than 50 years NLIDBs have been developed, their acceptance by end users is very low due to extremely complex problems inherent to natural language, their customization and internal operation, which has produced poor performance regarding queries correctly translated. This chapter presents a study on the main desirable features that NLIDBs should have as well as their pitfalls, describing some study cases that occur in some interfaces to illustrate the flaws of their approach.

On the Exact Solution of VSP for General and Structured Graphs: Models and Algorithms

In this chapter the vertex separation problem (VSP) is approached. VSP is NP-hard with important applications in VLSI, computer language compiler design, and graph drawing, among others. In the literature there are several exact approaches to solve structured graphs and one work that proposes an integer linear programming (ILP) model for general graphs. Nevertheless, the model found in the literature generates a large number of variables and constraints, and the approaches for structured graphs assume that the structure of the graphs is known a priori. In this work we propose a new ILP model based on a precedence representation scheme, an algorithm to identify whether or not a graph has a Grid structure, and a new benchmark of scale-free instances. Experimental results show that our proposed ILP model improves the average computing time of the reference model in 79.38 %, and the algorithm that identifies Grid-structured graphs has an effectiveness of 100 %.

Comparative Study on Constructive Heuristics for the Vertex Separation Problem

The vertex separation problem (VSP) consists of finding a linear ordering of the vertices of an input graph that minimizes the maximum number of vertex separators at each cut-point induced by the ordering. VSP is an NP-hard problem whose efficient solution is relevant in fields such as very large scale integration design, computer language compiler design, graph drawing and bioinformatics. In the literature reviewed, we found several exact algorithms and two metaheuristics based on the variable neighborhood search approach. These metaheuristics are currently the best stochastic algorithms for solving VSP. One of the key points of their efficiency is the usage of heuristics to construct a high-quality initial solution that considerably improves the algorithm performance. In this chapter we augment the literature on VSP by proposing a new set of heuristics. The proposed constructive heuristics are compared with the best ones found in the state-of-the-art and with random solution generator (Rnd). Experimental results demonstrate the importance of constructive algorithms. The best constructive improves Rnd by 89.96 % in solution quality.

A heterogeneous cellular processing algorithm for minimizing the power consumption in wireless communications systems

In this paper, the NP-hard problem of minimizing power consumption in wireless communications systems is approached. In the literature, several metaheuristic approaches have been proposed to solve it. Currently a homogeneous cellular processing algorithm and a GRASP algorithm hybridized with path-relinking are considered the state of the art algorithms. The main contribution of this paper is the analysis of five main characteristics for a heterogeneous cellular processing algorithm, based on scatter search and GRASP. A series of computational experiments with standard instances were carried out to assess the impact of each one of these characteristics. Among the main analyses we found particularly interesting a time reduction by 74.24%, produced by the stagnation detection characteristic. Also the communication characteristic improves the quality of the solutions by 24.73%. The B Héctor Joaquín Fraire Huacuja automatas2002@yahoo.com.mx J. David Terán-Villanueva david_teran01@yahoo.com.mx Juan Martín Carpio Valadez jmcarpio61@hotmail.com Rodolfo Pazos Rangel r_pazos_r@yahoo.com.mx Héctor José Puga Soberanes pugahector@yahoo.com José A. Martínez Flores jose.mtz@itcm.edu.mx 1 Instituto Tecnológico de León (ITL), Avenida Tecnológico s/No, C.P. 37290, León, Gto, Mexico 2 Instituto Tecnológico de Ciudad Madero (ITCM), Av. 1o. de Mayo s/No esq. Sor Juana Inés de la Cruz, C.P. 89440, Ciudad Madero, Tam, Mexico

A New Integer Linear Programming Model for the Cutwidth Minimization Problem of a Connected Undirected Graph

In this chapter we propose a new integer linear programming model based on precedences for the cutwidth minimization problem (CWP). A review of the literature indicates that this model is the only one reported for this problem. The results of the experiments with standard instances shows that the solution of the problem with the proposed model outperforms in quality and efficiency to the one reported in the state of the art. Our model increases the number of optimal solutions by 38.46 % and the gap reduction by 45.56 %. Moreover, this quality improvement is reached with a time solution reduction of 41.73 %. It is considered that the approach used in this work can be used in other linear ordering problems.

Mathematical Model for Optimizing the Composition of an Investment Portfolio for the Mexican Stock Market

A linear programming mathematical model is presented, which permits to compose an investment portfolio that achieves the maximal return at minimal risk from public information published on the web page of the Mexican stock exchange (BMV). Each of the linear programming problems (return maximization and risk minimization) is solved individually, and their optimal values are compared against those of a portfolio obtained using a statistical method. The results show that it is possible to compose a portfolio at minimal risk at time zero, and that the portfolio obtained by the statistical method is different from the one obtained by solving the optimization mathematical model.