Algorithms on strings
By M. Crochemore, C. Hancart, Thierry Lecroq. 2007
1,014 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/af8dc425bbc7eff3e0f814a062ce6fbe7317e0bf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Charu C. Aggarwal
- Raymond J. Mooney
- Luke S. Zettlemoyer
- Yuk Wah Wong
- Percy Liang
- Ruifang Ge
- Dawn Song
- Mirella Lapata
Citations in the corpus
- Compressed Suffix Trees with Full Functionality (2007, background): “Suffix trees are basic data structures for string algorithms [13].”
- Polygraph: automatically generating signatures for polymorphic worms (2005, methodology): “Many of the algorithms described in this section are based on algorithms found in [11].”
- Comparative experiments on learning information extractors for proteins and their interactions (2005, methodology): “Efficient algorithms for computing an LCS are presented in [10,23].”
- Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm (2005, neutral): “From these couplings accurate relative solute geometries and information about solute conformational change can be obtained.”
- A Survey of Text Clustering Algorithms (2012, background): “A suffix tree [45] is essentially a trie which contains all the suffixes of the entire collection.”
- The Algorithm Design Manual (2020, methodology): “• Gusfield [Gus97] – To my taste, this remains is the best introduction to string algorithms.”
- Fast Mapping of Short Sequences with Mismatches, Insertions and Deletions Using Index Structures (2009, background): “While suffix intervals correspond one-to-one to the nodes of a suffix trie for S $ (cf. [17]), lcp-intervals correspond to the branching nodes of a suffix tree for S $ (cf. [2]).”
- Time-series clustering - A decade review (2015, methodology): “Time-series Rj that minimizes E Ci;Rj is called a Steiner sequence [148].”
- Outlier Analysis (2013, methodology): “Suffix trees [196] are a classical data structure, which store all subsequences in a given database.”