List Of Suffixes Research Articles

Review Essay: The Sicilian World of Gaetano Cipolla

Review Essay: The Sicilian World of Gaetano Cipolla

Arabic light-based stemmer using new rules

Superior stemming algorithms aid significantly in many natural language processing (NLP) applications such as information retrieval. Arabic light-based stemmer is one of the most important stemming algorithms. However, partially due to the highly inflected and complexity of Arabic language morphological structure, most of the existing Arabic light-based stemmer algorithms eliminate a few numbers of suffixes and prefixes or both in the process of recognising the infix patterns to determine roots. The elimination of suffixes and prefixes leads to many inefficient results. Hence, this study aims to develop an improved light-based algorithm of the Arabic stemmer by proposing an appropriate suffixes and prefixes list, which is supported by rules according to word length (without using a morpheme or patterns on a stem). Our improved Dlight Arabic stemmer focuses on determining and removing the infix patterns under many rules on length-words and according to a specific order of the stages of the stemming to extract the double, triple and quadruple roots from long and short Arabic words. To evaluate our proposed light-based Arabic stemmer, we compared our stemmer against existing Arabic stemmers, namely Light10, Condlight and ARLST. The experimental results showed the proposed Develop Arabic Light-Based Stemmer (Dlight) obtained the best performance with 68% of F-measure, while the other three Arabic stemmers yield slightly lower F-measure. Finally, establishing an appropriate list of suffixes and prefixes with word length rules to stem Arabic words can improve the performance of a light-based Arabic stemmer.

Improving Semantic Coherence of Gujarati Text Topic Model Using Inflectional Forms Reduction and Single-letter Words Removal

A topic model is one of the best stochastic models for summarizing an extensive collection of text. It has accomplished an inordinate achievement in text analysis as well as text summarization. It can be employed to the set of documents that are represented as a bag-of-words, without considering grammar and order of the words. We modeled the topics for Gujarati news articles corpus. As the Gujarati language has a diverse morphological structure and inflectionally rich, Gujarati text processing finds more complexity. The size of the vocabulary plays an important role in the inference process and quality of topics. As the vocabulary size increases, the inference process becomes slower and topic semantic coherence decreases. If the vocabulary size is diminished, then the topic inference process can be accelerated. It may also improve the quality of topics. In this work, the list of suffixes has been prepared that encounters too frequently with words in Gujarati text. The inflectional forms have been reduced to the root words concerning the suffixes in the list. Moreover, Gujarati single-letter words have been eliminated for faster inference and better quality of topics. Experimentally, it has been proved that if inflectional forms are reduced to their root words, then vocabulary length is shrunk to a significant extent. It also caused the topic formation process quicker. Moreover, the inflectional forms reduction and single-letter word removal enhanced the interpretability of topics. The interpretability of topics has been assessed on semantic coherence, word length, and topic size. The experimental results showed improvements in the topical semantic coherence score. Also, the topic size grew notably as the number of tokens assigned to the topics increased.

Property Suffix Array with Applications in Indexing Weighted Sequences

The suffix array is one of the most prevalent data structures for string indexing; it stores the lexicographically sorted list of suffixes of a given string. Its practical advantage compared to the suffix tree is space efficiency. In Property Indexing , we are given a string x of length n and a property Π, i.e., a set of Π- valid intervals over x so that a pattern p occurs in x if and only if x has an occurrence of p that lies entirely within an interval of Π. A suffix-tree-like index over the valid prefixes of suffixes of x can be built in time and space O ( n ). We show here how to directly build a suffix-array-like index, the Property Suffix Array (PSA), in time and space O ( n ). We mainly draw our motivation from weighted (probabilistic) sequences: sequences of probability distributions over a given alphabet. Given a probability threshold 1/ z , we say that a string p of length m matches a weighted sequence x of length n at starting position i if the product of probabilities of the letters of p at positions i , …, i + m − 1 in x is at least 1/ z . Our algorithm for building the PSA can be directly applied to build an O ( nz )-sized suffix-array-like index over x in time and space O ( nz ). Finally, we present extensive experimental results showing that our new indexing data structure is well suited for real-world applications.

Parallel Computation of the Burrows-Wheeler Transform of Short Reads Using Prefix Parallelism.

The Burrows-Wheeler transform (BWT) of short-read data has unexplored potential utilities, such as for efficient and sensitive variation analysis against multiple reference genome sequences, because it does not depend on any particular reference genome sequence, unlike conventional mapping-based methods. However, since the amount of read data is generally much larger than the size of the reference sequence, computation of the BWT of reads is not easy, and this hampers development of potential applications. For the alleviation of this problem, a new method of computing the BWT of reads in parallel is proposed. The BWT, corresponding to a sorted list of suffixes of reads, is constructed incrementally by successively including longer and longer suffixes. The working data is divided into more than 10,000 "blocks" corresponding to sublists of suffixes with the same prefixes. Thousands of groups of blocks can be processed in parallel while making exclusive writes and concurrent reads into a shared memory. Reads and writes are basically sequential, and the read concurrency is limited to two. Thus, a fine-grained parallelism, referred to as prefix parallelism, is expected to work efficiently. The time complexity for processing n reads of length l is O(nl2). On actual biological DNA sequence data of about 100 Gbp with a read length of 100 bp (base pairs), a tentative implementation of the proposed method took less than an hour on a single-node computer; i.e., it was about three times faster than one of the fastest programs developed so far.

WORD-FORMATIVE MEANING OF ACTION SEMELFACTIVENESS IN THE KHANTY LANGUAGE (AS EXEMPLIFIED IN THE KAZYM DIALECT)

Study of verb formation holds a high position in the Finno-Ugric linguistics. In spite of works on the verb formation in other dialects of the Khanty language there are many gaps and uncovered issues in description of the Kazym dialect. Goal and tasks of the research. The main goal of the research is to find suffixes with the meaning of action semelfactiveness in the Kazym dialect of the Khanty language, to specify the list of suffixes and the meanings given to the verb. According to the goal stated the following tasks are completed in the work: 1. To collect factual material: verbs with the meaning of semelfactiveness using the sources of literature, colloquial and dialect speech. 2. To analyze and specify morphological characteristic of the semelfactive verbs 3. To detect productivity of the verb suffixes being studied and compare their semantics with other dialects of the Khanty language. Academic novelty. In this work we have examined considerable layer of semelfactive verbs that allows us to specify the meanings of suffixes, detect their productivity. Topicality of this research is explained by the fact that the issue of action semelfactiveness using the example of the Kazym dialect of the Khanty language has not been specially studied.

Suffix Trays and Suffix Trists: Structures for Faster Text Indexing

Suffix trees and suffix arrays are two of the most widely used data structures for text indexing. Each uses linear space and can be constructed in linear time for polynomially sized alphabets. However, when it comes to answering queries with worst-case deterministic time bounds, the prior does so in O(mlog|Σ|) time, where m is the query size, |Σ| is the alphabet size, and the latter does so in O(m+logn) time, where n is the text size. If one wants to output all appearances of the query, an additive cost of O(occ) time is sufficient, where occ is the size of the output. Notice that it is possible to obtain a worst case, deterministic query time of O(m) but at the cost of super-linear construction time or space usage. We propose a novel way of combining the two into, what we call, a suffix tray. The space and construction time remain linear and the query time improves to O(m+log|Σ|) for integer alphabets from a linear range, i.e. Σ⊂{1,…,cn}, for an arbitrary constant c. The construction and query are deterministic. Here also an additive O(occ) time is sufficient if one desires to output all appearances of the query. We also consider the online version of indexing, where the text arrives online, one character at a time, and indexing queries are answered in tandem. In this variant we create a cross between a suffix tree and a suffix list (a dynamic variant of suffix array) to be called a suffix trist; it supports queries in O(m+log|Σ|) time. The suffix trist also uses linear space. Furthermore, if there exists an online construction for a linear-space suffix tree such that the cost of adding a character is worst-case deterministic f(n,|Σ|) (n is the size of the current text), then one can further update the suffix trist in O(f(n,|Σ|)+log|Σ|) time. The best currently known worst-case deterministic bound for f(n,|Σ|) is O(logn) time.