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Learning unions of tree patterns using queries [chapter]

Hiroki Arimura, Hiroki Ishizaka, Takeshi Shinohara
1995 Lecture Notes in Computer Science  
We present an algorithm that exactly learns every concept in TPk in polynomial time in k and n using equivalence and membership queries, where n is the size of the longest counterexample given so far.  ...  This paper investigates efficient learning of TPk, the class of collections of at most k firstorder terms, where each collection defines the union of the sets of ground instances of each first-order term  ...  Learning unions of tree patterns using queries In this section, we first prove that there exists a polynomial time algorithm that correctly identifies any union in TPk using equivalence and restricted  ... 
doi:10.1007/3-540-60454-5_29 fatcat:tgnuyluhj5do7ok4dyhy2d73le

Learning unions of tree patterns using queries

Hiroki Arimura, Hiroki Ishizaka, Takeshi Shinohara
1997 Theoretical Computer Science  
We present an algorithm that exactly learns every concept in TPk in polynomial time in k and n using equivalence and membership queries, where n is the size of the longest counterexample given so far.  ...  This paper investigates efficient learning of TPk, the class of collections of at most k firstorder terms, where each collection defines the union of the sets of ground instances of each first-order term  ...  Learning unions of tree patterns using queries In this section, we first prove that there exists a polynomial time algorithm that correctly identifies any union in TPk using equivalence and restricted  ... 
doi:10.1016/s0304-3975(97)00015-7 fatcat:3gd4ew5mrngkplzbsfmp7q4gza

Learning of Finite Unions of Tree Patterns with Internal Structured Variables from Queries

S. MATSUMOTO, T. SHOUDAI, T. UCHIDA, T. MIYAHARA, Y. SUZUKI
2008 IEICE transactions on information and systems  
key words: exact learning, computational learning theory, finite union of tree pattern languages 1.  ...  Shinohara, •gLearning unions of tree patterns using queries,•h Theor. Comput. Sci., vol.185, pp. 47- 62,1997. [6] H. Arimura, H. Sakamoto, and S.  ... 
doi:10.1093/ietisy/e91-d.2.222 fatcat:6r2bja6ndvh6vfup3ifdhbqxbq

Learning of Finite Unions of Tree Patterns with Internal Structured Variables from Queries [chapter]

Satoshi Matsumoto, Takayoshi Shoudai, Tetsuhiro Miyahara, Tomoyuki Uchida
2002 Lecture Notes in Computer Science  
We consider the polynomial time learnability of finite unions of ordered tree patterns with internal structured variables, in the query learning model of Angluin (1988) .  ...  We show that any finite union of languages defined by m term trees is exactly identifiable in polynomial time using at most 2mn 2 restricted subset queries and at most m + 1 equivalence queries, where  ...  We give a polynomial time learning algorithm of finite unions of ordered tree patterns with internal structured variables, in the query learning model of Angluin [5] .  ... 
doi:10.1007/3-540-36187-1_46 fatcat:lucm5s6o6faz5eopuuj7u6qcxi

Page 8166 of Mathematical Reviews Vol. , Issue 2004j [page]

2004 Mathematical Reviews  
Every intersection of finitely many pattern languages can be represented as a union of pattern languages, but it may be a union of infinitely many ones.  ...  We consider the class PL‘ of unions of at most k intersections of finitely many pattern languages.  ... 

Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries

Satoshi Matsumoto, Yusuke Suzuki, Takayoshi Shoudai, Tetsuhiro Miyahara, Tomoyuki Uchida
2009 IPSJ Online Transactions  
We present polynomial time learning algorithms for finite unions of term trees with repeated variables by using superset and restricted equivalence queries.  ...  Moreover, we show that there exists no polynomial time learning algorithm for finite unions of term trees by using restricted equivalence, membership, and subset queries.  ...  We showed the polynomial time exact learnability of finite unions of linear term trees by using restricted subset queries and equivalence queries 11) .  ... 
doi:10.2197/ipsjtrans.2.250 fatcat:yqpynvfuxbdzvi2xxfzrfedjdq

Shape Classification Using Tree -Unions

Bo Wang, Wei Shen, Wenyu Liu, Xinge You, Xiang Bai
2010 2010 20th International Conference on Pattern Recognition  
We illustrate the utility of the proposed method on the problem of 2D shape classification using the new shape tree representation.  ...  A new shape tree based on junction nodes can represent the global structure in a simple way. The statistic distribution of junctions can be learned by merging the shape trees.  ...  We use each shape in this database as a query, and the other 3 shapes to learn and construct a shape tree union. Fig. 3 shows the classification result of our system.  ... 
doi:10.1109/icpr.2010.246 dblp:conf/icpr/WangSLYB10 fatcat:o46fbk4j5ncgzjt4cygp5wrhhu

Page 9545 of Mathematical Reviews Vol. , Issue 2003m [page]

2003 Mathematical Reviews  
Summary: “We present efficient on-line algorithms for learning unions of a constant number of tree patterns, unions of a constant number of one-variable pattern languages, and unions of a con- stant number  ...  Louis, MO); Kwek, Stephen S. (1-TXSA-C; San Antonio, TX) On learning unions of pattern languages and tree patterns in the mistake bound model.  ... 

On learning unions of pattern languages and tree patterns in the mistake bound model

Sally A. Goldman, Stephen S. Kwek
2002 Theoretical Computer Science  
We present e cient on-line algorithms for learning unions of a constant number of tree patterns, unions of a constant number of one-variable pattern languages, and unions of a constant number of pattern  ...  We prove that if arbitrary unions of pattern languages with ÿxed length substitutions can be learned e ciently then DNFs are e ciently learnable in the mistake bound model.  ...  We give an e cient algorithm to learn unions of a constant number of ordered tree patterns (in the mistake bound model without membership queries) in the presence of attribute noise.  ... 
doi:10.1016/s0304-3975(01)00402-9 fatcat:awgzad7vgbfaniqmq6hmw72b5q

Exact learning of unordered tree patterns from queries

Thomas R. Amoth, Paul Cull, Prasad Tadepalli
1999 Proceedings of the twelfth annual conference on Computational learning theory - COLT '99  
We consider learning tree patterns from queries ex-  ...  We thank Dana Angluin, David Page, Lisa Hellerstein, and Roni Khardon for interesting discussions on the topic of this paper. We thank the reviewers for many excellent suggestions on the paper.  ...  We consider learning tree patterns as well as finite unions of tree patterns, which we call forests.  ... 
doi:10.1145/307400.307486 dblp:conf/colt/AmothCT99 fatcat:cqy4e3a5wzb3bkhxv2yu4qvmea

Page 3353 of Mathematical Reviews Vol. , Issue 2001E [page]

2001 Mathematical Reviews  
We also present a learning algorithm for width-2 OBDDs that uses O(n) proper equivalence queries and O(n?) membership queries.  ...  We present a learn- ing algorithm for width-2 OBDDs, an algorithm which uses O(n’) equivalence queries alone, where n is the number of variables.  ... 

On Exact Learning of Unordered Tree Patterns

Thomas R. Amoth, Paul Cull, Prasad Tadepalli
2001 Machine Learning  
A finite union of tree patterns is called a forest. In this paper, we study the learnability of tree patterns from queries when the subtrees are unordered.  ...  Finally, we connect the problem of learning tree patterns to inductive logic programming by describing a class of tree patterns called Clausal trees that includes non-recursive single-predicate Horn clauses  ...  We thank Dana Angluin, Lisa Hellerstein, Roni Khardon, Stephen Kwek, David Page, Vijay Raghavan, and Chandra Reddy for interesting discussions on the topic of this paper.  ... 
doi:10.1023/a:1010971904477 dblp:journals/ml/AmothCT01 fatcat:7ekkj2zwirg5de632yzoblavkq

AutoSPARQL: Let Users Query Your Knowledge Base [chapter]

Jens Lehmann, Lorenz Bühmann
2011 Lecture Notes in Computer Science  
It uses supervised machine learning and allows users to ask queries without knowing the schema of the underlying knowledge base beforehand and without expertise in the SPARQL query language.  ...  We then present the AutoSPARQL user interface, which implements an active learning approach on top of QTL.  ...  Using them enables us to define a very efficient learning algorithm for SPARQL queries. Note that a query tree T does not contain cycles, whereas an RDF graph G can, of course, contain cycles.  ... 
doi:10.1007/978-3-642-21034-1_5 fatcat:vhxkbjk4tbfgdju24euf32clda

Page 6519 of Mathematical Reviews Vol. , Issue 98J [page]

1998 Mathematical Reviews  
unions of tree patterns using queries.  ...  The algorithm for this class uses only equivalence queries and it can also be used to learn the class of unions of O(1) boxes (from equivalence queries only).”  ... 

SQL Injection Attacks Predictive Analytics Using Supervised Machine Learning Techniques

Akinsola Jide E. T., Awodele Oludele, Idowu Sunday A., Kuyoro Shade O.
2020 International Journal of Computer Applications Technology and Research  
Machine Learning Approach requires a lot of data for efficient model training with capability for using several attack patterns.  ...  There are several solutions and approaches for identification and prevention of SQLIA, such as Cryptography, Extensible Markup Language (XML), Pattern Matching, Parsing and Machine Learning.  ...  Parse Tree Approach encompasses input type checking and pattern matching while machine learning approach encompasses input type checking, pattern matching and encoding input.  ... 
doi:10.7753/ijcatr0904.1004 fatcat:irmkqktyvna5fet345xtzhxif4
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