Convert text in specific format into real PHP code assignments - php

I'm having some problems to get a text in a specific format into real working PHP code.
My text file:
#T1:The German sociologist Max Weber once proposed
#S:Jos Bleau
#C:jos.bleau#domain.com
#L:"He used to be so conservative," she says, throwing up her hands in mock exasperation. "We used to have the worst arguments right here at this table. I was part of the first group of public city school teachers that struck to form a union, and Richard was very angry with me. He saw unions as corrupt. He was also very opposed to social security. He thought people could make much more money investing it on their own. Who knew that within 10 years he would become so idealistic
#R:At first, <#Ri>Stallman viewed these notices<#$p> with alarm. Rare was the software program that didn't borrow source code from past programs, and yet, with a single stroke of the president's pen, Congress had given programmers and companies the power to assert individual authorship over communally built programs. It also injected a dose of formality into what had otherwise been an informal system.
The AI Lab of the 1970s was by all accounts a special place. Cutting-edge projects and top-flight researchers gave it an esteemed position in the world of computer science. The internal hacker culture and its anarchic policies lent a rebellious mystique as well. Only later, when many of the lab's scientists and software superstars had departed, would hackers fully realize the unique and ephemeral world they had once inhabited.
As a single parent for nearly a decade-she and Richard's father, Daniel Stallman, were married in 1948, divorced in 1958, and split custody of their son afterwards-Lippman can attest to her son's aversion to authority. She can also attest to her son's lust for knowledge. It was during the times when the two forces intertwined, Lippman says, that she and her son experienced their biggest battles.
#ST:Fusions
#R:Such mythological descriptions, while extreme, underline an important fact. The ninth floor of 545 Tech Square was more than a workplace for many. For hackers such as Stallman, it was home.
The belief in individual freedom over arbitrary authority extended to school as well. Two years ahead of his classmates by age 11, Stallman endured all the usual frustrations of a gifted public-school student. It wasn't long after the puzzle incident that his mother attended the first in what would become a long string of parent-teacher conferences.
#ST:Fusions
#R:The belief in individual freedom over arbitrary authority extended to school as well. Two years ahead of his classmates by age 11, Stallman endured all the usual frustrations of a gifted public-school student. It wasn't long after the puzzle incident that his mother attended the first in what would become a long string of parent-teacher conferences.
#BV:Thirty years later, Breidbart remembers
#CP:(Picture: Credit – Jos Bleau) or #CP:(Picture: Thanks)
The expected output I need (Half pseudo code; Unescaped quotes):
<?php
$title1 = 'The German sociologist Max Weber once proposed';
$signature = 'Jos Bleau';
$email = 'jos.bleau#domain.com';
$lead = '"He used to be so conservative," she says, throwing up her hands in mock exasperation. "We used to have the worst arguments right here at this table. I was part of the first group of public city school teachers that struck to form a union, and Richard was very angry with me. He saw unions as corrupt. He was also very opposed to social security. He thought people could make much more money investing it on their own. Who knew that within 10 years he would become so idealistic';
$text[] = 'At first, <#Ri>Stallman viewed these notices<#$p> with alarm. Rare was the software program that didn't borrow source code from past programs, and yet, with a single stroke of the president's pen, Congress had given programmers and companies the power to assert individual authorship over communally built programs. It also injected a dose of formality into what had otherwise been an informal system.
The AI Lab of the 1970s was by all accounts a special place. Cutting-edge projects and top-flight researchers gave it an esteemed position in the world of computer science. The internal hacker culture and its anarchic policies lent a rebellious mystique as well. Only later, when many of the lab's scientists and software superstars had departed, would hackers fully realize the unique and ephemeral world they had once inhabited.
As a single parent for nearly a decade-she and Richard's father, Daniel Stallman, were married in 1948, divorced in 1958, and split custody of their son afterwards-Lippman can attest to her son's aversion to authority. She can also attest to her son's lust for knowledge. It was during the times when the two forces intertwined, Lippman says, that she and her son experienced their biggest battles.';
$subtitle[] = 'Fusions';
//etc...
?>
Note:
The names like $title1 and #T1 are completely unrelated to each other and $title1 is just used as example. It could also be $xy or something else
If #XY appears more than once in the file then the values should be added as array element, else as simple assignment
I don't know if preg_split() is the correct direction and I can do it with it? Or do I have to use other functions to accomplish this?

Explanation
First we get the data from the text file into a variable with file_get_contents() and also initialize our $output array, where each element is a line in the output, with a php tag <?php.
You can also modify $lookup with shortcut => variable name elements, where you can define which #XY: gets replaced with which variable name. If not defined the shortcut will be used as variable name.
Now that we have prepared some stuff we match each #XY: with the corresponding data with preg_match_all().
Regular Expression
/#(\w+):(.*?)(?=#\w+:)/s
\w+ matches all word characters \[a-zA-Z0-9_\], which is the XY part from #XY: and we keep it with a capturing group
+ is a quantifier and says that \w should match 1 or more times
(.*?) matches everything as much as needed
With the flag s, * also matches new lines
(?=#\w+:) makes sure (.*?) matches everything until the next #XY: and not more. Where ?= is a positive lookahead and as it says it looks ahead if that regex in the parentheses(#\w+) can be matched
We also preemptively save the amount each shortcut appears in the data with array_count_values().
Now that we have matched all data which we want we can loop through all shortcuts, which are saved in $m[1]. In the foreach loop we simply check if you have defined a lookup variable name or if we use the shortcut as variable name.
Then we simply add each assignment as new element to the output array. Where you have to note three things:
Complex (curly) syntax is used, so that you don't get problems with invalid variable names, see: How can I access a property with an invalid name?
Depending on how many times a shortcut appeared in the data we decide if it should be added as array element or normal assignment. If the shortcut appears more than once in the data it will be adding the value as array element else as simple string assignment
We use trim() to remove spaces, new lines, ... from the start and end of the string. And we use addslashes(), so we don't get problems with quotes
Done. And now we are already done. Just depending on how you want to output the result you can save it to a file with file_put_contents() or just print out the array.
Code
<?php
$text = file_get_contents("test.txt");
$output = ["<?php"];
$lookup = []; //Example: ["ST" => "subtitle"]
preg_match_all("/#(\w+):(.*?)(?=#\w+:)/s", $text, $m);
$variableShortcutCount = array_count_values($m[1]);
foreach($m[1] as $key => $variableShortcut){
if(isset($lookup[$variableShortcut])){
$output[] = '${"' . $lookup[$variableShortcut] . ($variableShortcutCount[$variableShortcut] > 1 ? '"}[]' : '"}') . " = '". addslashes(trim($m[2][$key])) . "';" ;
} else {
$output[] = '${"' . $variableShortcut . ($variableShortcutCount[$variableShortcut] > 1 ? '"}[]' : '"}') . " = '". addslashes(trim($m[2][$key])) . "';" ;
}
}
//Output to file
//file_put_contents("output.txt", implode(PHP_EOL, $output));
//Output to browser
echo "<pre><code>";
highlight_string(implode(PHP_EOL, $output));
?>
output:
<?php
${"T1"} = 'The German sociologist Max Weber once proposed';
${"S"} = 'Jos Bleau';
${"C"} = 'jos.bleau#domain.com';
${"L"} = '\"He used to be so conservative,\" she says, throwing up her hands in mock exasperation. \"We used to have the worst arguments right here at this table. I was part of the first group of public city school teachers that struck to form a union, and Richard was very angry with me. He saw unions as corrupt. He was also very opposed to social security. He thought people could make much more money investing it on their own. Who knew that within 10 years he would become so idealistic';
${"R"}[] = 'At first, <#Ri>Stallman viewed these notices<#$p> with alarm. Rare was the software program that didn\'t borrow source code from past programs, and yet, with a single stroke of the president\'s pen, Congress had given programmers and companies the power to assert individual authorship over communally built programs. It also injected a dose of formality into what had otherwise been an informal system.
The AI Lab of the 1970s was by all accounts a special place. Cutting-edge projects and top-flight researchers gave it an esteemed position in the world of computer science. The internal hacker culture and its anarchic policies lent a rebellious mystique as well. Only later, when many of the lab\'s scientists and software superstars had departed, would hackers fully realize the unique and ephemeral world they had once inhabited.
As a single parent for nearly a decade-she and Richard\'s father, Daniel Stallman, were married in 1948, divorced in 1958, and split custody of their son afterwards-Lippman can attest to her son\'s aversion to authority. She can also attest to her son\'s lust for knowledge. It was during the times when the two forces intertwined, Lippman says, that she and her son experienced their biggest battles.';
${"subtitle"}[] = 'Fusions';
${"R"}[] = 'Such mythological descriptions, while extreme, underline an important fact. The ninth floor of 545 Tech Square was more than a workplace for many. For hackers such as Stallman, it was home.
The belief in individual freedom over arbitrary authority extended to school as well. Two years ahead of his classmates by age 11, Stallman endured all the usual frustrations of a gifted public-school student. It wasn\'t long after the puzzle incident that his mother attended the first in what would become a long string of parent-teacher conferences.';
${"subtitle"}[] = 'Fusions';
${"R"}[] = 'The belief in individual freedom over arbitrary authority extended to school as well. Two years ahead of his classmates by age 11, Stallman endured all the usual frustrations of a gifted public-school student. It wasn\'t long after the puzzle incident that his mother attended the first in what would become a long string of parent-teacher conferences.';
${"BV"} = 'Thirty years later, Breidbart remembers';
${"CP"} = '(Picture: Credit – Jos Bleau) or';

Related

Parsing, formatting and generating data based on input

For some known inputs I have some known outputs/results. Based on this I want the program to generate result based on the input as per pre-filled input-results data.
Example input:
Enjoy your tea in the morning then have some bread in the lunch. Enjoy the taste of a garlic chicken in the dinner.
Your day starts with cold coffee. In the noon have some rice and fish curry.
Example output:
Have tea in the morning. Have some bread in the lunch. Have garlic chicken in the dinner.
Have cold coffee. Have some rice and fish curry.
I don't want to use string replace or regexp as it will break often. How or where do I start ?
If you have a large number of input and output pairs, you can treat this as a sequence to sequence task. The input can be considered your source and output can be considered as a target. You can easily develop a baseline model using OpenNMT.
Not really clear on your how to approach your specific problem, but let me go about a few ways to solve text related issues, since it seems to be what you are interested at.
Level 0 Static text hashing
IF, and that's a big if, your input is static, you could have digests maping inputs to outputs. But, as you mentioned, this is easily breakable. Even one extra space would result in a mismatch and that's why it's level 0.
Level 1 Pre-process your input:
Remove all extra spaces before, after and in-between words.
Remove stopwords from your input:
List of common stop-words https://www.textfixer.com/tutorials/common-english-words.txt
This step would transform your input to:
Enjoy tea morning bread lunch. Enjoy taste garlic chicken dinner.
day starts cold coffee. noon rice fish curry.
Next you could remove verbal conjugation, which doesn't apply to your example, but let's assume you had a sentences like:
drink tea, drank juice and drinks soda.
This sentence your become:
drink tea, drink juice drink soda
You could go even deeper and have synonyms normalization, example:
drink tea, sip water, slurped a juice, swallow beer
Then, all of them would become:
drink tea, drink water, drink juice, drink beer
After these steps are done, you have kind of a non statistical way of processing text. It all comes down to removing any redundancy and language flourish and getting down to the literal stuff.
And, of course, this approach loses a ton of the value contained in the english language. You can't tell sarcasm, you can't have analogies. So, this works for some domains, but it's not that advanced.
This approach is more about text processing and not language processing. See the difference?
If you need a smarter way to go about this, you should look into full text search algorithms
Level 2 Full text search algorithms
There are several ways to do this, here is one.
You've got a sentence like:
I want pizza
This search term would become
want piz za
And would search for
want piz
piz za
want za
This is super basic stuff, and it's just to show you how raw text processing works and ways you could go about this. Maybe you could have your inputs processed by level 1 to make them simpler and less variable and then have them processed by level 2 to be indexed in a db and then you have a nice way to query them
Level 3 NLP - Natural Language Processing
This is still not machine learning, but it is smarter and it's built on top of all the other steps. basically you would clean your inputs of nonsense and try to apply english gramatical structure to it.
To know more: https://dev.to/nicfoxds/getting-started-in-nlp-b0e
level 4 Deep learning stuff
Basically, google.
You get a bunch of text, a bunch of search queries, a bunch of user tracking data mapping queries to text. You feed all of that into a neural network and statistical models will detect patterns for you and make your search better as it goes.
Summary
If this is a project are serious about, look into NLU. It will give you a decent outcome as you track usage. Then, when you have enough user data, go for the deep learning stuff.
There's no easy way around this, you either do this by hand or implement a database that has some of those features, like elasticsearch. But as one of the comments mentioned, php is not a language for this.
If your input is truly known, then you can use str_replace() e.g.
$input = 'Enjoy your tea in the morning then have some bread in the lunch. Enjoy the taste of a garlic chicken in the dinner.
Your day starts with cold coffee. In the noon have some rice and fish curry.';
$old = array('Enjoy your ', ' then have ', '. Enjoy the taste of a ', 'Your day starts with ', '. In the noon have ');
$new = array('Have ' , '. Have ' , '. Enjoy ' , 'Have ' , '. Have ' );
$output = str_replace($old, $new, $input);
Beware of case sensitivity and things like spaces, periods and other punctuation.
If your input is less known, then you could use regex as you surmised.

Levenshtein - grouping hotel names

I have to group some hotel into the same category based on their names. I'm using levenshtein for grouping, but how much I've tried, some hotel are leaved outside the category they supposed to be, or in another category.
For example: all these hotel should be in the same category:
=============================
Best Western Bercy Rive Gauche
Best Western Colisee
Best Western Ducs De Bourgogne
Best Western Folkestone Opera
Best Western France Europe
Best Western Hotel Sydney Opera
Best Western Paris Louvre Opera
Best Western Hotel De Neuville
=============================
I'm having a list with all hotel names( like 1000 rows ). I also have how they should be grouped.
Any idea how to optimize levenshtein, making it more flexible for my situation?
$inserted = false;
foreach($hotelList as $key => $value){
if (levenshtein($key, $hotelName, 2, 5, 1) <= abs(strlen($key) - strlen($hotelName))){
array_push($hotelList[$key], trim($line));
$inserted = true;
}
}
// if no match was found add another entry
if (!$inserted){
$hotelList[$hotelName] = array(
trim($line)
);
}
I'll wade in with my thoughts. Firstly, grouping or "clustering" data like this is a pretty big topic, I won't really go into it particularly but perhaps point things in an ideal direction.
You did a brilliant thing by normalizing Levenshtein on the length of the strings compared- that's exactly right because you avoid the problem that the length of the string would overdetermine the similarity in many cases.
But the algorithm didn't solve the problem. For a start, we want to compare words. "Bent Eastern French Hotels" is obviously very different to "Best Western French Hotels", yet it would score better than "Best Western Paris Bed and Breakfasts", say. The intution to grasp here is that your tokens shouldn't be characters but words.
I like #saury's answer, but I'm not sure about the assumption at the beginning. Instead, let's start with something nice and easy often called "bag of words". We then implement a hashing trick, which would allow you to idetify the key phrases based on the intuition that the least used words contain the most information.
If you subscribe to the idea that hotel brand names are near the beginning you could always skew on their proximity to the start of the string too. Thing is, your groups will as likely end up being "France" as "Best" / "Western" (but not "hotel"- why?).
You want your results to be more accurate?
From here on in, we're gonna have to take a step up to some serious algorithms- enjoy surfing the many stack overflow topics. My instinct is that I bet many hotel names aren't branded at all, so you'll need different categories for them too. And my instinct is also that the number of repeated words in hotel names is going to be relatively slim- some words will be frequent members of hotel names. These facts would be problems for the above. In this case, there's a really popular (if cliched for SO) technique called k-means, a fun introduction to which would be to extend an algorithm like this (very bravely written in php) to take your chosen n keyphrases as the n dimensions of the cluster, then take the majority components of the cluster center-points as your categorization tags. (That would eliminate "France", say, because hits for "France" would be spread across the n-dimensional space pretty evenly).
This is probably all a bit much to take on for something that would seem like a small problem- but I want to emphasize that if your data isn't structured, there really aren't any short-cuts to doing things properly.
what levenshtein distance value do you take as the delta between words to be treated as part of same group ? Seems that you tend to group hotels based on the initial few words and that will require a different approach altogether (like do dictionary sort , compare current string with next strings etc). However if your use-case still requires to calculate levenshtein distance then I would suggest you to sort the Strings based on their length and then start comparing each string with other strings of similar length (apply you own heuristic to what you consider as 'similar' like you may say isSimilar = Math.abs(str1.length - str2.length) < SOME_LOWEST_DELTA_VALUE or something like that)
You might want to read about http://en.wikipedia.org/wiki/K-means_clustering and http://en.wikipedia.org/wiki/Cluster_analysis in general.

php: Regex and the caret

So I'm trying to make a regex to include the course contents of a text, but exclude the 3 digit numbers followed by a period and some text. Basically I'm trying to divide the course text into individual courselines, so that I end up with an array where every element has the courseinfo of one class.
For example, suppose we have:
$text = "295. Student-Initiated Courses or Projects. (1-2)
Open to students who have completed the first-year curriculum. Clinical work, field work, legal assistance, individual research and writing, writing or editing for profes¬sional journals, student-taught courses, or other legal projects of a serious, educational nature. Requires the approval of the Law 295 Administrator and the Dean.
296. Legal Dissertation. (8-13)"
and this giant regex:
$lineDelimiter = ='/(?:[0-9]{3}(?:\.5|\-[1-5])?[A-Z]?)(?:\-[0-9]{3}(?:\.5|\-[0-9])? [A-Z]?)?\.\s*.+\.\s*(?:(?:\([0-9]+\-*[0-9]*\))(?:\s*or\s*\([0-9]+\-*[0-9]*\))?)?\s*(?:Prerequisite)?.+(?:\n.+)?\.\n?(?:\s*Mr\.\s.+,?|\s*Ms\.\s.+,?|\s*Dr\.\s.+,?|\s*The\sFaculty.*,?)*[^(?:[0-9]{3}\..+)]/';
The very last part of that giant regex, which consists of
'/[^(?:[0-9]{3}\..+)]/'
errors when I preg_match_all.
I'm trying to exclude the "296. Legal Dissertation. (8-13)" part so that it will be
"295. Student-Initiated Courses or Projects. (1-2)
Open to students who have completed the first-year curriculum. Clinical work, field work, legal assistance, individual research and writing, writing or editing for profes¬sional journals, student-taught courses, or other legal projects of a serious, educational nature. Requires the approval of the Law 295 Administrator and the Dean."
If you want to match everything except the last part with the number and the text you could try this:
'/([\s\S]+)(?=\d{3}\..+)/'
[\s\S]+ matches everything - both whitespace and non-whitespace
(?=) performs Positive Lookahead. It does not match the things in the brackets, but it makes sure the stuff before the brackets is followed by this in the brackets.
\d{3}\..+ matches 3 digits followed by a dot and some other characters without new lines.

Named entity recognition with preset list of names for Python / PHP

I'm trying to process a CSV file that has as in each row a text field with the name of organization and position of an individual within that organization as unstructured text. This field is usually a mess of text like this:
Assoc. Research Professor Dept. Psychology Univ. California Santa Barbara
I need to pull out the position and the organization name. For the position, I use preg_match for a series of about 60 different regular expressions for the different professions, and I think it works pretty well (my guess is that it catches about 80%). But, I'm having trouble catching the organization name. I have a MySQL table with roughly 16,000 organization names that I can perform a simple preg_match for, but due to common misspellings and abbreviations, it's only catching about 30% of the organizations. For example, my database has
University of California Santa Barbara
But the CSV file might have any of the options:
Univ Cal Santa Barbara
University Cal-Santa Barbara
University California-Santa Barbara
Cal University, Santa Barbara
I need to process several hundred thousand records, and I can't spend the time to correct 70% of the records that are currently not being processed correctly or painstakingly create multiple aliases for each organization. What I would like to be able to do is to catch small differences (such as the small misspellings, hyphens versus spaces, and common abbreviations), and, if still no matches are found, to ideally recognize an organizational name and create a new record for it.
What libraries or tools in Python or PHP would allow to perform a similarity match that would have a broader reach?
Would NLTK in Python catch misspellings?
Is it possible to use AlchemyAPI to catch misspelled organizations? So far I've only been able to use it to catch correctly spelled organizations
Since I'm comparing a short string (the organization name) to a longer string (that includes the name plus extraneous information) is there any hope in using PHP's similar_text function?
Any help or insight would be appreciated.
This is within the domain of fuzzy logic. See if these are of any help:
http://www.phpclasses.org/blog/post/119-Neural-Networks-in-PHP.html
http://ann.thwien.de/index.php/Installation
You may be able to use difflib to calculate the similarity ratio between the CSV input and the canonical spelling, and consider it a match if it's above a certain threshold (say, 0.65).
For example:
import difflib
exact = 'University of California Santa Barbara'
inputs = ['Univ Cal Santa Barbara',
'University Cal-Santa Barbara',
'University California-Santa Barbara',
'Cal University, Santa Barbara',
'Canterbury University']
sm = difflib.SequenceMatcher(None, exact)
ratios = []
for input in inputs:
sm.set_seq2(input)
ratios.append(sm.ratio())
print ratios
gives:
[0.73333333333333328, 0.81818181818181823, 0.93150684931506844,
0.71641791044776115, 0.33898305084745761]
Note how 'Canterbury University' has a much lower match ratio() than the inputs you gave.
Then again, SequenceMatcher.ratio() may be too slow computed over 16,000 values.

Tricky file parsing. Inconsistent Delimeters

I need to parse a file with the following format.
0000000 ...ISBN.. ..Author.. ..Title.. ..Edit.. ..Year.. ..Pub.. ..Comments.. NrtlExt Nrtl Next Navg NQoH UrtlExt Urtl Uext Uavg UQoH ABS NEB MBS FOL
ABE0001 0-679-73378-7 ABE WOMAN IN THE DUNES (INT'L ED) 1st 64 RANDOM 0.00 13.90 0.00 10.43 0 21.00 10.50 6.44 3.22 2 2.00 0.50 2.00 2.00 ABS
The ID and ISBN are not a problem, the title is. There is no set length for these fields, and there are no solid delimiters- the space can be used for most of the file.
Another issue is that there is not always an entry in the comments field. When there is, there are spaced within the content.
So I can get the first two, and the last fourteen. I need some help figuring out how to parse the middle six fields.
This file was generated by an older program that I cannot change. I am using php to parse this file.
I would also ask myself 'How good does this have to be' and 'How many records are there'?
If, for example, you are parsing this list to put up a catalog of books to sell on a website - you probably want to be as good as you can, but expect that you will miss some titles and build in feedback mechanism so your users can help you fix the issue ( and make it easy for you to fix it in your new format).
On the other hand, if you absolutely have to get it right because you will loose lots of money for each wrong parse, and there are only a few thousand books, you should plan on getting close, and then doing a human review of the entire file.
(In my first job, we spend six weeks on a data conversion project to convert 150 records - not a good use of time).
Find the title and publisher of the book by ISBN (in some on-line database) and parse only the rest :)
BTW. are you sure that what looks like space actually is a space? There are more "invisible" characters (like non-break space). I know, not a good idea, but apparently author of that format was pretty creative...
You need to analyze you data by hand and find out what year, edition and publisher look like. For example if you find that year is always two digits and publisher always comes from some limited list, this is something you can start with.
While I don't see any way other then guessing a bit I'd go about it something like this:
I'd scale off what I know I can parse out reliably. Leaving you with ABE WOMAN IN THE DUNES (INT'L ED) 1st 64 RANDOM
From there I'd try locate the Edition and split the string into two at that position after storing and removing the Edition leaving you with ABE WOMAN IN THE DUNES (INT'L ED) & 64 RANDOM, another option is to try with the year but of course Titles such as 1984 might present a problem . (Guessing edition is of course assuming it's 7th, 51st etc for all editions).
Finally I'd assume I could somewhat reliable guess the year 64 at the start of the second string and further limit the Publisher(/Comment) part.
The rest is pure guesswork unless you got a list of authors/publishers somewhere to match against as I'd assume there are not only comments with spaces but also publishers with spaces in their names. But at least you should be down to 2 strings containing Author/Title in one and Publisher(/Comments) in the other.
All in all it should limit the manual part a bit.
Once done I'd also save it in a better format somewhere so I don't have to go about parsing it again ;)
I don't know if the pcre engine allows multiple groups from within selection, therefore:
([A-Z0-1]{7})\ (\d-\d{3}-\d{5}-\d)\
(.+)\ (\d(?:st|nd|rd))\ \d{2}\
([^\d.]+)\ (\d+.\d{2})\ (\d+.\d{2})\
(\d+.\d{2})\ (\d+.\d{2})\ (\d{1})\
(\d+.\d{2})\ (\d+.\d{2})\ (\d+.\d{2})\
(\d+.\d{2})\ (\d)\ (\d+.\d{2})\
(\d+.\d{2})\ (\d+.\d{2})\ (\d+.\d{2})\
(\w{3})
It does look quite ugly and doesn't fix your author-title problem but it matches quite good for the rest of it.
Concerning your problem I don't see any solution but having a lookup table for authors or using other services to lookup title and author via the ISBN.
Thats if unlike in your example above the authors are not just represented by their first name.
Also double check all exception that might occur with the above regex as titles may contain 1st or alike.

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