Syntactic and Semantic Matching Sample Clauses

Syntactic and Semantic Matching. ‌ Text-based methods perform syntactic and semantic matching between nat- ural language texts in several ways. Early tree-based methods for text appli- cations emerged in the early 1980s [134]. This family of approaches is based on a distance paradigm: two syntactic trees are similar to each other if the minimum cost of required sequence modifications (add, delete, change) is relatively small. Punyakanok et al. [104] were one of the firsts who used syn- tactic tree matching applications to question answering. This idea has been further extended to fuzzy relation matching based on statistical models [38]. Several other extensions to the tree-based approaches have been presented in the current literature [148, 164, 10]. 3xxxx://xxx.xxxx.xxx/ Tree kernels for syntactic structures have been well studied in the appli- cation of question answering. Xxxxxxx and Xxxxx [59] developed a heuristic method based on a tree kernel to find shorter and more intuitive sequences. These approaches are often more compact than the initial tree-edit distances, because they are based on prebuilt tree structural cores that define possible tree modifications. Tree kernels have been further researched in [94, 97, 95]. Semantic parsing is another field that has attracted a lot of attention in question answering and has been widely used. Two semantic roles cor- pora are commonly known: PropBank [102] and FrameNet [5]. After parsing natural language texts and obtaining their semantic annotations, it is easier to understand the semantic meaning of the text. One of the first attempts focused on structured probabilistic inference using predicate- arguments pairs [99]. More recently, Shen et al. have shown significant performance gains when semantic roles are combined with syntax-based sys- tems. [125]. All the aforementioned work describes the background in using the syntactic and semantic information to improve the question answering systems. This dissertation presents several new techniques that are built on the foundation of research in this field and provide significant performance boosts in various tasks.
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