IEEE Transactions on Pattern Analysis and Machine Intelligence
A Winnow-Based Approach to Context-Sensitive Spelling Correction
Machine Learning - Special issue on natural language learning
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Pronunciation modeling for improved spelling correction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Fast Approximate Search in Large Dictionaries
Computational Linguistics
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Exploring distributional similarity based models for query spelling correction
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Learning a spelling error model from search query logs
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficient Merging and Filtering Algorithms for Approximate String Searches
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Space-Constrained Gram-Based Indexing for Efficient Approximate String Search
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient top-k algorithms for fuzzy search in string collections
Proceedings of the First International Workshop on Keyword Search on Structured Data
A discriminative candidate generator for string transformations
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using the web for language independent spellchecking and autocorrection
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Real-word spelling correction using Google Web IT 3-grams
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Machine learning for query-document matching in search
Proceedings of the fifth ACM international conference on Web search and data mining
Beyond bag-of-words: machine learning for query-document matching in web search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Fast multi-task learning for query spelling correction
Proceedings of the 21st ACM international conference on Information and knowledge management
| Hi-index | 0.00 |
This paper proposes a new method for approximate string search, specifically candidate generation in spelling error correction, which is a task as follows. Given a misspelled word, the system finds words in a dictionary, which are most "similar" to the misspelled word. The paper proposes a probabilistic approach to the task, which is both accurate and efficient. The approach includes the use of a log linear model, a method for training the model, and an algorithm for finding the top k candidates. The log linear model is defined as a conditional probability distribution of a corrected word and a rule set for the correction conditioned on the misspelled word. The learning method employs the criterion in candidate generation as loss function. The retrieval algorithm is efficient and is guaranteed to find the optimal k candidates. Experimental results on large scale data show that the proposed approach improves upon existing methods in terms of accuracy in different settings.