dataesr/scientific-paragraphs-categorization huggingface dataset:
Thus, the creation of morphologically annotated Amharic corpus is a long-sought resource for the research community. Morphological annotation of a language is the process of assigning linguistic information such as part-of-speech (POS) and morphological features to recognize each word in a document  [33]. Morphological analyzers can help to automatically annotate text corpus. With regard to Amharic, there have been few attempts to develop morphological analyzers  [16, 21, 22]. These tools are at a prototype stage and they are also limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools. The objective of this research work is:  (1)  to promote publicly accessible Amharic resources including a standard test collection for IR, morphologically annotated corpora and compiled stopwords list; and (2) to design Amharic IR system by investigating the optimal representation of documents and queries considering both root-based and stem-based text representations. The rest of this paper is organized as follows. Section 2 describes Amharic language and its morphology. Section 3 discusses related work. In Section 4, we present the proposed Amharic IR system architecture along with various options to represent Amharic documents and queries.
Thousands of words can be generated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The majority of words in the language are generated from verbal roots. Nouns, adjectives, and adverbs can be derived from verbal roots. The derivation of words from verbal roots usually u/, / Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be generated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The majority of words in the language are generated from verbal roots. Nouns, adjectives, and adverbs can be derived from verbal roots. The derivation of words from verbal roots usually i/, / Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be generated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The majority of words in the language are generated from verbal roots. Nouns, adjectives, and adverbs can be derived from verbal roots. The derivation of words from verbal roots usually a/, / Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be generated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The majority of words in the language are generated from verbal roots. Nouns, adjectives, and adverbs can be derived from verbal roots. The derivation of words from verbal roots usually e/, / Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes difficult to create annotated corpus automatically. Moreover, there is lack of standa reference collection making it a major impediment to the development of Amharic IR an NLP tools.
Amharic Writing System Amharic is the working language of the government of Ethiopia currently having a estimated population of over 117 million  [34]. It is the second most commonly spok Semitic language in the world after Arabic  [35]. Although many languages are spoken Ethiopia, Amharic is the lingua franca and the most literary language serving as a m dium of instruction in the education system of the country for a long period. Amhar uses Ethiopic alphabet and has 34 base characters along with modifications on the r spective base characters. The alphabet is conveniently written in a tabular format seven columns. The first column represents the basic form with vowel ኧ /ə/ and t other six orders represent modifications with vowels in the order of ኡ / ʔ u/, ኢ /ʔi/, ኣ ʔa/, ኤ /ʔe/, እ /ʔɨ/, and ኦ /ʔo/.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually t sas r l. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually kwat Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually w Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually n Appl. Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually na/ is constructed from four prefixes ( /j preposition/, / W 3 of 29 mited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it ifficult to create annotated corpus automatically. Moreover, there is lack of standard ference collection making it a major impediment to the development of Amharic IR and LP tools.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually negation/, / 2, 12, x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Sci. 2022,  12,  x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools. The objective of this research work is:  (1)  to promote publicly accessible Amharic resources including a standard test collection for IR, morphologically annotated corpora and compiled stopwords list; and (2) to design Amharic IR system by investigating the optimal representation of documents and queries considering both root-based and stem-based text representations. The rest of this paper is organized as follows. Section 2 describes Amharic language and its morphology. Section 3 discusses related work.
Moreover, there is lack of standard eference collection making it a major impediment to the development of Amharic IR and LP tools. The objective of this research work is:  (1)  to promote publicly accessible Amaric resources including a standard test collection for IR, morphologically annotated orpora and compiled stopwords list; and (2) to design Amharic IR system by investiating the optimal representation of documents and queries considering both root-based nd stem-based text representations. The rest of this paper is organized as follows. Section 2 describes Amharic language nd its morphology. Section 3 discusses related work. In Section 4, we present the proosed Amharic IR system architecture along with various options to represent Amharic ocuments and queries. Section 5 presents the evaluation framework of the proposed mharic adhoc retrieval system including the presentation of the resources and corpora, xperimental setup, and experimental results.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually w , x FOR PEER REVIEW 3 of 29 limited in scope. The unavailability of full-fledged low-level Amharic NLP tools makes it difficult to create annotated corpus automatically. Moreover, there is lack of standard reference collection making it a major impediment to the development of Amharic IR and NLP tools.
Thousan of words can be gener-ated from an Amharic root or its stems by changing the shape characters in a stem or root, inserting vowels between root radicals, reduplicating one the characters of the stem or word itself, and by adding affixes on stems  [22]. There multiple stem templates for verbal words. However, all variants have a single r representation template. The major-ity of words in the language are generated from ver roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation words from verbal roots usually k ru/, etc. Amharic verbal stems are formed from verbal roots by inserting vowels between radicals (consonants). For example, the verbal stems /n Ethiopia, Amharic is the lingua franca and the most literary language serving as a medium of instruction in the education system of the country for a long period.
Thousands ords can be gener-ated from an Amharic root or its stems by changing the shape of acters in a stem or root, inserting vowels between root radicals, reduplicating one of characters of the stem or word itself, and by adding affixes on stems  [22]. There are tiple stem templates for verbal words. However, all variants have a single root esentation template. The major-ity of words in the language are generated from verbal s. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of ds from verbal roots usually /, and ----/s--k--r-Amharic is the working language of the government of Ethiopia currently having an estimated population of over 117 million  [34]. It is the second most commonly spoken Semitic language in the world after Arabic  [35]. Although many languages are spoken in Ethiopia, Amharic is the lingua franca and the most literary language serving as a medium of instruction in the education system of the country for a long period.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually / CVCC Jussive /s ls. The objective of this research work is: (1) to promote publicly accessible Amources including a standard test collection for IR, morphologically annotated and compiled stopwords list; and (2) to design Amharic IR system by investie optimal representation of documents and queries considering both root-based -based text representations.
Thousands can be gener-ated from an Amharic root or its stems by changing the shape of s in a stem or root, inserting vowels between root radicals, reduplicating one of cters of the stem or word itself, and by adding affixes on stems  [22]. There are stem templates for verbal words. However, all variants have a single root tation template. The major-ity of words in the language are generated from verbal uns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of m verbal roots usually b r tools. The objective of this research work is: (1) to promote publicly accessible Amresources including a standard test collection for IR, morphologically annotated ra and compiled stopwords list; and (2) to design Amharic IR system by investig the optimal representation of documents and queries considering both root-based tem-based text representations.
Thousands rds can be gener-ated from an Amharic root or its stems by changing the shape of cters in a stem or root, inserting vowels between root radicals, reduplicating one of aracters of the stem or word itself, and by adding affixes on stems  [22]. There are ple stem templates for verbal words. However, all variants have a single root sentation template. The major-ity of words in the language are generated from verbal Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of s from verbal roots usually / CCVC /f l NLP tools. The objective of this research work is: (1) to promote publicly accessible Amharic resources including a standard test collection for IR, morphologically annotated corpora and compiled stopwords list; and (2) to design Amharic IR system by investigating the optimal representation of documents and queries considering both root-based and stem-based text representations.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually g NLP tools. The objective of this research work is: (1) to promote publicly accessible Amharic resources including a standard test collection for IR, morphologically annotated corpora and compiled stopwords list; and (2) to design Amharic IR system by investigating the optimal representation of documents and queries considering both root-based and stem-based text representations.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually / CVCC /mar NLP tools. The objective of this research work is: (1) to promote publicly accessible Amharic resources including a standard test collection for IR, morphologically annotated corpora and compiled stopwords list; and (2) to design Amharic IR system by investigating the optimal representation of documents and queries considering both root-based and stem-based text representations.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually k NLP tools. The objective of this research work is: (1) to promote publicly accessible Amharic resources including a standard test collection for IR, morphologically annotated corpora and compiled stopwords list; and (2) to design Amharic IR system by investigating the optimal representation of documents and queries considering both root-based and stem-based text representations.
Thousands of words can be gener-ated from an Amharic root or its stems by changing the shape of characters in a stem or root, inserting vowels between root radicals, reduplicating one of the characters of the stem or word itself, and by adding affixes on stems  [22]. There are multiple stem templates for verbal words. However, all variants have a single root representation template. The major-ity of words in the language are generated from verbal roots. Nouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of words from verbal roots usually / CVCC Gerund /s b lt to create annotated corpus automatically. Moreover, there is lack of standard ce collection making it a major impediment to the development of Amharic IR and ols. The objective of this research work is: (1) to promote publicly accessible Amesources including a standard test collection for IR, morphologically annotated a and compiled stopwords list; and (2) to design Amharic IR system by investithe optimal representation of documents and queries considering both root-based m-based text representations.
Thousands ds can be gener-ated from an Amharic root or its stems by changing the shape of ers in a stem or root, inserting vowels between root radicals, reduplicating one of racters of the stem or word itself, and by adding affixes on stems  [22]. There are le stem templates for verbal words. However, all variants have a single root ntation template. The major-ity of words in the language are generated from verbal ouns, adjectives, and ad-verbs can be derived from verbal roots. The derivation of from verbal roots usually r ult to create annotated corpus automatically. Moreover, there is lack of standard nce collection making it a major impediment to the development of Amharic IR and tools. The objective of this research work is: (1) to promote publicly accessible Amresources including a standard test collection for IR, morphologically annotated ra and compiled stopwords list; and (2) to design Amharic IR system by investig the optimal representation of documents and queries considering both root-based tem-based text representations.